CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

About the Team: Mission Engineering at CHAOS turns simulation output into decisions. We run large-scale modeling and simulation campaigns across all warfighting domains and the full kill chain, against named threats, in operationally relevant scenarios, at the speed engineering, operational, and customer teams actually need. Every CHAOS engineering trade, pursuit, and customer engagement is anchored in rigorous, physics-based, tactically relevant, and statistically valid analysis, and we're scaling the function to meet that bar across a growing product portfolio.

About the Role: On the Mission Engineering team at CHAOS, you will design, develop, execute, analyze, and validate models and simulations to deliver operational analysis and system performance assessment across defense, national security, and commercial programs. You will have freedom to move rapidly and use your expertise to apply rigorous statistical methods to analyze simulation outcomes, quantify system effectiveness, and communicate actionable insights to technical teams, leadership, and customers. Your work will directly inform critical decisions around sensor performance, mission planning, weapon effectiveness, and platform capability evaluation.

This is a foundational hire. You will shape how CHAOS does mission analysis from day one, and you will have the freedom to move fast.

What You'll Do:

• Scope, plan, and execute modeling and simulation efforts and studies aligned to program objectives, managing your competing priorities and timelines effectively.
• Develop, configure, and execute analysis using mission-level models and simulations such as AFSIM, ESAMS, Brawler, Ansys STK, and/or physics-based models to evaluate system and platform performance in operationally relevant scenarios.
• Build and refine models of sensors, communications systems, aircraft (including unmanned), weapons, and spacecraft within mission-level simulation frameworks.
• Architect, implement, and validate models of both blue and red systems, sensors, communications, weapons, aircraft, spacecraft, and ground/maritime platforms, within mission- and engagement-level simulation frameworks.
• Define and apply rigorous statistical methodologies to simulation results to quantify measures of effectiveness and performance to produce relevant and defensible findings for internal and external stakeholders.
• Develop and maintain Python-based analysis tools and pipelines for data processing, statistical analysis, and visualization.
• Implement technical methodology, simulation best practices, and customer engagement.
• Document methodology, assumptions, and findings in technical reports and briefing materials, including data visualizations, and present results to both technical and non-technical audiences.
• Partner with engineering, product, growth, and customer teams to translate operational questions into well-structured analytical approaches and shape new business pursuits. Push back when the framing is wrong.

Minimum Requirements:

• Bachelor's degree or higher in Computer Science, Aerospace/Software/Computer Engineering, Data Science, Statistics, Mathematics, Operations Research, Physics, or a related field.
• 5+ years of experience supporting defense, intelligence, or advanced technology programs through industry or government employment.
• Demonstrated track record leading mission-level operations analysis studies and delivering decision-quality results to senior engineering and customer stakeholders.
• Extensive direct experience with combat simulations such as AFSIM, ESAMS, Brawler, Ansys STK, or equivalent, including ownership of rigorous methodology, not just execution.
• Significant experience developing analytical tools and applying rigorous statistical methods to interpret and present results.
• Strong proficiency in Python and MATLAB, including standard scientific computing libraries (such as Pandas, Polars, NumPy, SciPy, Scikit-Learn, Matplotlib, Seaborn, CuPy, or PyTorch).
• Exceptional data visualization skills and comfort developing CONOPS/OV-1 visuals and briefing packages.
• Proficiency with software development practices including version control and leveraging/validating outputs of AI-assisted coding tools.
• Demonstrated ability to lead analytical efforts and deliver products with minimal oversight, including leading projects and studies.
• Comfortable working on Linux-based systems and writing scalable scripts and software.
• Exceptional written and verbal communication skills, including experience briefing flag/general officer or SES-level audiences.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance 

Preferred Requirements:

• Active TS/SCI clearance.
• Recognized expertise analyzing the full kill chain (find, fix, track, target, engage, assess) across multiple domains, including air-to-air, air-to-surface, surface-to-air, space, and electronic warfare engagements.
• Deep expertise in sensor performance analysis (especially radar) and in developing and validating models of sensors, communications, weapons, aircraft, spacecraft, or ground/maritime systems in mission-level simulation environments such as AFSIM or Ansys STK.
• Experience leading study teams or technical working groups across organizations, including model accreditation, V&V efforts, or threat-informed scenario development.
• Experience designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting system effectiveness or kill chain assessment.
• Exposure to Distributed Interactive Simulation (DIS) networking and visualization tools such as MAK VR-Forces, SIMDIS, or similar.
• Experience supporting rapid development programs across DoD services, DARPA, ONR, AFRL, COCOMs, the acquisition community, or commercial advanced technology programs.
• Experience supporting capture and positioning activities (RFI/RFP responses, white papers, technical exchanges) and shaping new business pursuits.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

About the Team: Mission Engineering at CHAOS turns simulation output into decisions. We run large-scale modeling and simulation campaigns across all warfighting domains and the full kill chain, against named threats, in operationally relevant scenarios, at the speed engineering, operational, and customer teams actually need. Every CHAOS engineering trade, pursuit, and customer engagement is anchored in rigorous, physics-based, tactically relevant, and statistically valid analysis, and we're scaling the function to meet that bar across a growing product portfolio.

About the Role: You will own statistical methodology for the Mission Engineering team at CHAOS. You'll design experimental constructs that extract meaningful signals from broad trade studies and computationally expensive simulation runs, build the analytical pipelines the team relies on, push the methodological state of the art on how we characterize uncertainty, build surrogate models, and communicate quantitative results to decision-makers. You will work shoulder-to-shoulder with engineers and experts in every domain to ensure that simulated, experimental, and tactical results presented by CHAOS are rigorous, reproducible, and actually deliver answers that our teams, customers, and partners need

This is a foundational hire. You will have the freedom to move fast and set the standards for how CHAOS does quantitative analysis from day one.

What You'll Do:

• Design rigorous experimental constructs (DOE, space-filling designs, adaptive sampling, sequential experimentation) for large-scale simulation campaigns, getting maximum signal per simulation hour across operationally relevant trade spaces.
• Apply advanced statistical methods (such as regression modeling, Bayesian inference, surrogate/metamodeling, sensitivity analysis, uncertainty quantification, and beyond) to simulation output to produce decision-quality conclusions.
• Build and own scalable Python-based data pipelines for ingestion, processing, statistical analysis, and visualization of large simulation datasets.
• Develop ML and statistical surrogate models that accelerate analysis, enable real-time trade studies, and feed mission planning applications.
• Set team standards for data management, reproducibility, and statistical rigor (such as code review, methodology validation, and documentation practices).
• Translate operational and engineering questions into well-structured analytical approaches alongside M&S engineers, threat SMEs, and program staff. Push back when the framing is wrong.
• Author technical reports and briefing materials with clear, honest data visualizations; present quantitative results to senior technical and non-technical audiences in language they can act on.
• Mentor peers and cross-functional teams on experimental design, statistical methodology, and reproducible analysis.
• Support programs spanning DoD services, DARPA, intelligence community, and commercial customers.

Required Qualifications:

• Bachelor's degree or higher in Statistics, Data Science, Mathematics, Artificial Intelligence, a related quantitative field, or equivalent demonstrated expertise in modern statistical methodology.
• 7+ years applying advanced statistical and data science methods, ideally supporting defense, intelligence, or advanced technology programs.
• Deep working expertise in experimental design, regression and Bayesian methods, uncertainty quantification, and surrogate modeling, not just textbook familiarity.
• Strong proficiency working in Python, including scientific computing and ML libraries (especially Pandas, Polars, NumPy, SciPy, Scikit-Learn, Statsmodels, PyMC, Matplotlib, Seaborn, CuPy, PyTorch), and exposure to MATLAB or R.
• Demonstrated experience building scalable analytical pipelines for large datasets, including comfort with terabyte-scale data and modern dataframe tooling.
• Exceptional data visualization skills and the ability to develop briefing-quality technical products.
• Strong software development practices: version control, code review, reproducible workflows, and informed use of AI-assisted coding tools.
• Track record of working independently, taking ownership of ambiguous problems, and delivering with minimal oversight.
• Comfortable working with Linux operating systems and writing scalable scripts/software.
• Exceptional written and verbal communication skills, especially in translating quantitative approaches and results for non-technical audiences.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance.

Preferred Qualifications:

• Master's or PhD in Statistics, Data Science, Mathematics, Artificial Intelligence, or a related quantitative field.
• Direct experience applying statistical methods to outputs from military simulations including high fidelity engineering models, war games, and engagement or mission-level combat simulations such as AFSIM, ESAMS, Brawler, or Ansys STK.
• Expertise designing and analyzing large-scale Monte Carlo and DOE-driven simulation campaigns supporting full kill chain or system effectiveness assessment.
• Experience in developing surrogate models, simulations, machine learning, or artificial intelligence models for engineering and operations analysis applications.
• Familiarity with sensor performance analysis (radar, EO/IR, RF, acoustic), weapon effectiveness analysis, or mission-level engagement analysis.
• Experience with HPC environments and distributed computing frameworks (including scalable cloud services and GPU-accelerated computing).
• Leadership experience: mentoring or leading project teams through complex analytical efforts.
• Substantial experience in communicating statistical methods to both technical and non-technical stakeholders and decisionmakers.
• Experience supporting rapid development programs for DoD contractors, combatant commands, research labs, and acquisition communities.
• Active TS/SCI clearance.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

Position

Are you a passionate Software Engineer looking to bring cutting-edge software solutions to drug discovery? Join our mission to bring novel therapeutics to patients and be at the forefront of driving innovation through technology. As a Software Engineer 2, you will leverage your expertise to develop and implement software solutions that drive our groundbreaking scientific initiatives.

About You

The ideal candidate for this role thrives at the intersection of software and scientific discovery. You are proficient with production-quality Python codebases and can contribute to, maintain, and extend these codebases in a robust and scalable way. At the same time, you understand the fast pace of scientific discovery, and can collaborate with scientists to clarify requirements, focus on result rather than implementation, and keep projects moving forward. You are a strong communicator, especially to non-engineers, as well as a strong team player, always ready to pitch in to help a colleague. You are a continual learner with a growth mindset, eager to learn from your colleagues and expand your talents in a supportive environment and are excited about our mission to bring drugs to patients.

What You’ll Do

• Work with scientists to understand data generated by early drug discovery projects and provide custom analyses and/or production software solutions to answer key questions about the data.
• Build, maintain, and extend tools that deliver machine-learning-based as well as classical algorithmic solutions to scientists.
• Contribute to the continuous improvement of software development processes, tools, and methodologies.
• Conduct thorough code reviews, promoting best practices and identifying opportunities for code optimization and enhancement.
• Collaborate with team members, sharing insights and fostering a culture of knowledge sharing and learning.
• Uphold ethical and data privacy standards in all software engineering activities.

Qualifications

• BS in Computer Science, Mathematics, Physics, Bioinformatics, Biophysics, or a related field, plus 2 years of relevant experience, or equivalent work experience.
• Demonstrated experience (2+ years) with Python; familiarity with scientific programming packages (pandas, numpy) and/or machine learning frameworks (TensorFlow) a plus.
• Undergraduate level biology knowledge required; experience manipulating and analyzing biologically relevant data sets strongly desired (e.g. sequencing data, cellular imaging data, etc).
• Introductory coursework on deep learning or other modern ML approaches, or equivalent work experience, a plus.
• Familiarity with basic software best practices (CI/CDD, unit testing, version control, etc.) highly preferred.
• Strong analytical and problem-solving skills, with the ability to think critically and creatively to overcome technical challenges.
• Effective communication skills to collaborate with diverse teams, both technical and non-technical, especially across disciplines.
• Demonstrated ability to thrive in a fast-paced, dynamic work environment.

At Eikon, employee compensation also includes bonus and equity compensation, in addition to several generous benefit programs, including:​

• 401k plan with company matching​
• Medical (premiums covered by Eikon at 95%), dental and vision insurance (premiums covered by Eikon at 100%)​
• Mental health and wellness benefits​
• Weeklong summer and winter holiday shutdowns​
• Generous paid time off and holiday policies​
• Life/AD&D Insurance (premiums covered by Eikon at 100%) and optional supplemental employee-paid life/AD&D policies ​
• Enhanced parental leave benefit​
• Daily subsidized lunch program when on-site​

The expected salary range for this role is $135,000 to $147,250 depending on skills, competency, and the market demand for your expertise.

Data at Brex

The Data organization develops insights, models, and data infrastructure for teams across Brex, including Sales, Marketing, Product, Engineering, and Operations. Our Data Scientists, Analysts, and Engineers work together to make data—and insights derived from data—a core asset across the company.

What you’ll do

As a senior Data Analyst (DA III), you will own the end-to-end analytics lifecycle for one or more business areas at Brex. You’ll go beyond building dashboards—you’ll frame the right questions, design rigorous analyses, apply statistical methods, and translate your findings into clear recommendations for leadership. You will also serve as a technical leader on the Data Analytics team, mentoring more junior analysts and helping define the standards and best practices that elevate the team’s work.

This role sits at the intersection of analytics, analytics engineering, and business strategy. You’ll work in a modern data stack environment and partner closely with Data Scientists, Data Engineers, and senior leaders across the organization.

Where you’ll work

This role will be based in our San Francisco office. We are a hybrid environment that combines the energy and connections of being in the office with the benefits and flexibility of working from home. We currently require a minimum of three coordinated days in the office per week, Monday, Wednesday and Thursday. As a perk, we also have up to four weeks per year of fully remote work!

Responsibilities

• Own the analytics lifecycle for assigned business areas: from problem framing and data sourcing through analysis, insight generation, and stakeholder presentation.
• Build and maintain dashboards and self-service reporting tools that enable business teams to independently track performance, identify risks, and make data-driven decisions.
• Write production-quality SQL and Python code to extract, transform, and analyze data at scale.
• Collaborate with Data Engineers and Data Scientists to develop and maintain analytical data models, improve data pipelines, and ensure data quality across the organization.
• Partner with leadership across Sales, Operations, Product, Finance, and other departments to identify high-impact analytical opportunities and deliver actionable recommendations.
• Mentor other data analysts and contribute to the development of team standards, documentation, code review practices, and analytical frameworks.
• Proactively identify gaps in data infrastructure, propose improvements, and contribute to the evolution of the team’s tooling and processes.

Requirements

• 5+ years of experience in data analytics, business intelligence, or a related quantitative role.
• 3+ years of experience partnering directly with Sales, Operations, Product, or equivalent business teams as an embedded analytics partner.
• Advanced SQL proficiency, including CTEs, window functions, performance optimization, and working across complex data models.
• Proficiency in Python for data analysis, automation, and modeling (Pandas, NumPy, scikit-learn, or similar).
• Experience with cloud data warehouses, particularly Snowflake (BigQuery and Databricks also valued).
• Hands-on experience with BI and data visualization tools (Looker, Tableau, Hex, or similar).
• Strong stakeholder management skills—proven ability to present complex technical findings to non-technical audiences.
• Experience with generative AI and LLM-based tools (Claude Code, Cursor, GitHub Copilot) to perform and accelerate analyses, automated reporting, and build self-service data tools.

Bonus points

• Demonstrated experience applying statistical methods to business problems (e.g., regression, classification, A/B testing).
• Experience with dbt for data modeling and transformation.
• Experience building and maintaining data pipelines using orchestration tools such as Airflow.
• Experience working with APIs for data ingestion and integration.
• Familiarity with version control systems (Git).
• Experience in fintech, financial services, or payments.
• Track record of leading cross-functional analytics projects from scoping through delivery.

Compensation

The expected salary range for this role is $114,192 - $142,740. However, the starting base pay will depend on a number of factors including the candidate’s location, skills, experience, market demands, and internal pay parity. Depending on the position offered, equity and other forms of compensation may be provided as part of a total compensation package.

Brex LLC is a wholly owned subsidiary of Capital One, N.A.

About the team  

Our Warfighter Systems division is pioneering a future where mixed reality (MR), creates immersive, intuitive, and life-saving technologies. By seamlessly integrating real-time data with cutting-edge visualization tools, we are empowering warfighters with unparalleled situational awareness, enhanced training experiences, and operational superiority. This team is consistently pushing the boundaries of what's possible and shaping a future where technology and defense unite to protect our nation.  If this starts to excite you, we invite you to read further!

About the job  

We are seeking a highly skilled and experienced Systems Engineer to design, develop, and validate sophisticated models for our complex electro-mechanical systems, with a particular focus on sensors, cameras, and displays. The ideal candidate will leverage first-principles physics, empirical data, and advanced mathematical techniques to create high-fidelity, predictive models used across the entire product lifecycle – from concept exploration and design optimization to control system development and virtual testing. This role is critical in accelerating our product development cycles, improving system performance, and ensuring robust and reliable operation. 

What you'll do

• Model Development: 
  • Develop mathematical and behavioral models for various sensor types (e.g., IMU, Lidar, Radar, Ultrasonic, environmental sensors), capturing characteristics such as noise, latency, calibration, field of view, and transfer functions.
  • Create detailed camera models, encompassing optics, image signal processing pipelines, distortion, resolution, dynamic range, and temporal characteristics.
  • Integrate individual component models into comprehensive system-level simulations, accurately representing their interactions and overall system dynamics.
  • Develop and maintain Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) simulation environments. 

• Model Validation & Calibration:
  • Design and execute experiments to gather real-world data for model parameter identification, calibration, and validation.
  • Perform rigorous statistical analysis to quantify model accuracy, uncertainty, and fidelity against empirical measurements.
  • Identify discrepancies between model predictions and real-world behavior and iteratively refine models for improved accuracy. 

• Performance Analysis & Optimization:
  • Conduct trade-off studies using models to optimize system architecture, component selection, and control strategies based on performance, cost, power consumption, and reliability metrics.
  • Predict system performance under various operating conditions and environmental factors.
  • Perform sensitivity analyses to understand the impact of individual parameters on overall system behavior.
  • Support root cause analysis of system issues using simulation. 

• Collaboration & Communication:
  • Collaborate closely with cross-functional teams including Electrical, Mechanical, Controls, Software, and Test Engineers to define model requirements and integrate models into the broader development process.
  • Clearly communicate complex modeling concepts, results, and limitations to both technical and non-technical stakeholders through presentations and detailed documentation. 

• Tooling & Methodologies:
  • Select, evaluate, and implement appropriate modeling and simulation tools and techniques.
  • Develop custom scripts and tools to enhance modeling capabilities and automate workflows.
  • Stay abreast of industry best practices, new modeling methodologies, and emerging simulation technologies. 

Required Qualifications

• 6+ years of experience in system modeling, simulation, and analysis, particularly with electro-mechanical systems.
• Demonstrated experience in developing models for at least two of the following:

• • Sensors: IMUs (accelerometers, gyros), Lidars, Radars, Ultrasonic sensors, microphones, etc. (noise characteristics, drift, latency, sensor fusion).
  • Cameras: Optical models, image processing pipeline models, distortion, noise, dynamic range, rolling shutter effects.
  • Display: See/pass-through near eye display architectures, optical modeling, validations, & human perception 

• Strong theoretical foundation in classical and modern control systems, dynamics, signal processing, and numerical methods.
• Proficiency in primary modeling and simulation tools such as MATLAB/Simulink (Simscape a plus), Python (SciPy, NumPy, Pandas), or C/C++.
• Experience with model validation against experimental data and statistical analysis techniques.
• Excellent problem-solving skills, with an ability to apply first principles to complex engineering challenges.
• Strong communication and interpersonal skills, with the ability to work effectively in a team environment. Strong technical communication skills to collaborate effectively with cross-functional teams. 
• U.S. Person Status: Due to government contract requirements, candidates must be a U.S. Person (U.S. Citizen or Green Card holder).
• Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, Physics, or a related quantitative field. 

Preferred Qualifications

• Ph.D. in a relevant engineering or scientific discipline.
• Familiarity with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing methodologies and platforms (e.g., dSPACE, National Instruments).
• Knowledge of advanced control techniques (e.g., adaptive control, optimal control, robust control) and estimation algorithms (e.g., Kalman filters, particle filters).
• Experience with machine learning techniques for model identification, surrogate modeling, or data-driven predictions.
• Exposure to systems engineering processes, requirements management, and configuration control.

About the team  

Our Warfighter Systems division is pioneering a future where mixed reality (MR), creates immersive, intuitive, and life-saving technologies. By seamlessly integrating real-time data with cutting-edge visualization tools, we are empowering warfighters with unparalleled situational awareness, enhanced training experiences, and operational superiority, primarily through our EagleEye augmented reality system. This team is consistently pushing the boundaries of what's possible and shaping a future where technology and defense unite to protect our nation.  If this starts to excite you, we invite you to read further!

About the job  

We are seeking a highly skilled and experienced Systems Engineer to design, develop, and validate sophisticated models for our complex electro-mechanical systems, with a particular focus on sensors, cameras, and displays. The ideal candidate will leverage first-principles physics, empirical data, and advanced mathematical techniques to create high-fidelity, predictive models used across the entire product lifecycle – from concept exploration and design optimization to control system development and virtual testing. This role is critical in accelerating our product development cycles, improving system performance, and ensuring robust and reliable operation. 

What you'll do

• Model Development: 
  • Develop mathematical and behavioral models for various sensor types (e.g., IMU, Lidar, Radar, Ultrasonic, environmental sensors), capturing characteristics such as noise, latency, calibration, field of view, and transfer functions.
  • Create detailed camera models, encompassing optics, image signal processing pipelines, distortion, resolution, dynamic range, and temporal characteristics.
  • Integrate individual component models into comprehensive system-level simulations, accurately representing their interactions and overall system dynamics.
  • Develop and maintain Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) simulation environments. 

• Model Validation & Calibration:
  • Design and execute experiments to gather real-world data for model parameter identification, calibration, and validation.
  • Perform rigorous statistical analysis to quantify model accuracy, uncertainty, and fidelity against empirical measurements.
  • Identify discrepancies between model predictions and real-world behavior and iteratively refine models for improved accuracy. 

• Performance Analysis & Optimization:
  • Conduct trade-off studies using models to optimize system architecture, component selection, and control strategies based on performance, cost, power consumption, and reliability metrics.
  • Predict system performance under various operating conditions and environmental factors.
  • Perform sensitivity analyses to understand the impact of individual parameters on overall system behavior.
  • Support root cause analysis of system issues using simulation. 

• Collaboration & Communication:
  • Collaborate closely with cross-functional teams including Electrical, Mechanical, Controls, Software, and Test Engineers to define model requirements and integrate models into the broader development process.
  • Clearly communicate complex modeling concepts, results, and limitations to both technical and non-technical stakeholders through presentations and detailed documentation. 

• Tooling & Methodologies:
  • Select, evaluate, and implement appropriate modeling and simulation tools and techniques.
  • Develop custom scripts and tools to enhance modeling capabilities and automate workflows.
  • Stay abreast of industry best practices, new modeling methodologies, and emerging simulation technologies. 

Required Qualifications

• 9+ years of experience in system modeling, simulation, and analysis, particularly with electro-mechanical systems.
• Demonstrated experience in developing models for at least two of the following:

• • Sensors: IMUs (accelerometers, gyros), Lidars, Radars, Ultrasonic sensors, microphones, etc. (noise characteristics, drift, latency, sensor fusion).
  • Cameras: Optical models, image processing pipeline models, distortion, noise, dynamic range, rolling shutter effects.
  • Display: See/pass-through near eye display architectures, optical modeling, validations, & human perception 

• Strong theoretical foundation in classical and modern control systems, dynamics, signal processing, and numerical methods.
• Proficiency in primary modeling and simulation tools such as MATLAB/Simulink (Simscape a plus), Python (SciPy, NumPy, Pandas), or C/C++.
• Experience with model validation against experimental data and statistical analysis techniques.
• Excellent problem-solving skills, with an ability to apply first principles to complex engineering challenges.
• Strong communication and interpersonal skills, with the ability to work effectively in a team environment. Strong technical communication skills to collaborate effectively with cross-functional teams. 
• U.S. Person Status: Due to government contract requirements, candidates must be a U.S. Person (U.S. Citizen or Green Card holder).
• Bachelor's or Master's degree in Electrical Engineering, Mechanical Engineering, Robotics, Aerospace Engineering, Physics, or a related quantitative field. 

Preferred Qualifications

• Ph.D. in a relevant engineering or scientific discipline.
• Familiarity with Hardware-in-the-Loop (HIL) and Software-in-the-Loop (SIL) testing methodologies and platforms (e.g., dSPACE, National Instruments).
• Knowledge of advanced control techniques (e.g., adaptive control, optimal control, robust control) and estimation algorithms (e.g., Kalman filters, particle filters).
• Experience with machine learning techniques for model identification, surrogate modeling, or data-driven predictions.
• Exposure to systems engineering processes, requirements management, and configuration control.

About Wholesail ⛵️

Wholesale trade, a $55T global market, still operates like the world before the internet and modern payment networks: collection processes are manual and run on paper, short-term credit risk is assumed by the vendor, and businesses rely heavily on legacy ERP systems that don't talk to each other. The result is large, measurable drag — we estimate that vendors spend over $500B a year globally across industries on an inefficient mix of processing, bad debt, lending, credit insurance, software, and labor costs to get paid.

Wholesail is building a financial network from the ground up that connects the systems of vendors and buyers involved in wholesale trade to enable streamlined payment and the transfer of risk to third parties. This will allow vendors to offload risk and eliminate tens of billions of waste — while giving creditworthy buyers better terms and third-party capital, unlocking hundreds of billions (ultimately trillions) in additional sales. The primitives of this network scale across industries and geographies: a universal approach to ERP integrations, modern payment rails, and a live trade-credit bureau to underwrite risk — which we're calling Lighthouse.

The Opportunity: Risk & Capital Products 🚢

Credit is the load-bearing beam of our network. Every time a vendor ships goods before getting paid, someone is taking a risk — today it's the vendor, tomorrow it should be a third party at a fair price. Getting that transfer right is what unlocks the next order of magnitude of sales across the wholesale economy, and the only way to get it right is to underwrite buyers more accurately than anyone else in the industry. Listen to the Visa episode of the Acquired podcast to learn how credit card networks did this for retail trade. 

We think we're uniquely positioned to do this. Through Lighthouse, we're building a live, reciprocal trade-credit bureau: vendors on our network contribute real-time payment behavior on a long tail of SMB buyers that no traditional bureau sees. That data — combined with the bank, ERP, and transaction signals already flowing through Wholesail — is a modeling dataset that doesn't exist anywhere else. The first MLE on this team gets to decide what we build with it.

The problems are real and the stakes are significant. Our models directly shape the terms buyers are offered and the losses Wholesail and our capital partners absorb. There's no established playbook here and no legacy stack to inherit — you'll be setting the direction for how we do modeling, data engineering, and production ML at Wholesail for years to come.

The Role ⚒️

As the founding MLE on the Risk Engineering & Capital Products team, you'll own credit risk modeling end-to-end — from problem framing and data pipeline design, through model development and validation, through production serving and monitoring. You'll work directly with the hiring manager, our engineering and product leadership, and our hands-on advisor Dan Massoni (former Chief Commercial Credit Officer of American Express) to decide what to build, explore features to model and how you’ll scale our approach risk scoring. .

Expect your work to span:

• Modeling. Design, build, and validate credit risk models (PD, LGD, EAD, fraud, exposure sizing, pricing) against our proprietary reciprocal-bureau data and external signals. Choose the right tool for the job — gradient-boosted trees, deep models, LLMs, or classical statistical models — and defend the choice.
• Data engineering. Build the pipelines, feature logic, and training datasets that your models (and future models) run on. At this stage, the MLE owns the full data path; over time we'll grow a team around you.
• Productionization. Ship models into production systems where they make real decisions on real dollars. Own deployment, monitoring, drift detection, and iteration.
• Partnering cross-functionally. Work closely with product, engineering, capital markets, and external lending and insurance partners. Explain your models to people who care about the outcomes but not the math, and translate their constraints back into modeling decisions.
• Shaping the team. Help define the hiring bar and interview process for the data scientists and MLEs who will join after you. You'll have a strong voice in what this team becomes.

Qualifications

• 5+ years of experience building models for production use cases.
• Deep modeling skill: strong command of supervised learning on tabular data, including feature engineering, model selection, hyperparameter tuning, calibration, and rigorous offline and online evaluation.
• Strong data engineering skills — comfortable owning ETL and feature pipelines end-to-end against real, messy production data (SQL and a modern data-processing stack).
• Proficiency in Python and the modern ML ecosystem (pandas, scikit-learn, PyTorch or TensorFlow, XGBoost/LightGBM, Jupyter, etc.).
• Solid statistical reasoning — you can spot leakage, selection bias, label noise, and spurious correlations, and you know why your offline metric doesn't always predict online performance.
• Track record of owning models end-to-end: not just prototyping in a notebook, but taking something from a problem statement to a production system that makes decisions.
• Excellent written and spoken English communication skills; ability to explain model behavior, tradeoffs, and limitations to non-ML audiences (product, ops, capital partners, leadership).
• The spirit of a team player who believes in fostering a healthy and supportive work environment.

Bonus Qualifications

• Direct experience in credit risk modeling — PD/LGD/EAD models, scorecards, underwriting models, exposure management, or collections modeling — particularly for SMB or subprime segments.
• Experience in fintech, lending, payments, fraud, or insurance, or with regulated modeling environments (model risk management, adverse action, fair lending).
• Experience building or operating ML platform components — feature stores, model registries, training orchestration, online serving, monitoring/drift detection.
• Backend engineering depth: comfortable writing production services, designing APIs, and reasoning about distributed systems that consume your models.
• Strong data analysis background — fluency in exploratory analysis, experimentation, and translating data into product and business decisions.
• Experience with LLMs and agentic systems applied to operational problems (document understanding, KYB, entity resolution, agent tooling).
• Experience as the first or founding ML hire at a company, or early on a team that had to build ML infrastructure from scratch.
• Published research, Kaggle placements, or prominent OSS contributions in the ML or data ecosystem.
• BA or BS in Computer Science, Statistics, Mathematics, a related technical field, or equivalent practical experience.
• Advanced degree (MS or PhD) in a quantitative field.

Equal Employment Opportunity

Wholesail is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of race, color, religion, national origin, sex, gender identity or expression, sexual orientation, age, marital status, veteran status, disability status, pregnancy, or any other characteristic protected by federal, state, or local law. Employment decisions at Wholesail are based on qualifications, merit, and business needs. We encourage applicants from all backgrounds to apply.

Role Description

As a Senior Value Engineer specializing in the Public Sector, you are pushing the envelope in solving critical operational challenges for State and Local Government agencies. You will be working with our most strategic public sector clients, understanding their unique objectives—from enhancing citizen services and modernizing legacy systems to optimizing grant management and regulatory compliance—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.

With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the complex realities of government operations (breaking down agency silos) and enables agencies to industrialize AI. This unlocks real ROI on AI deployments, maximizing taxpayer value at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to government CIOs and Agency Directors, and ensure successful implementation, adoption, and value realization to increase the footprint of Celonis across state and local governments.

Key Responsibilities:

• AI Discovery & Solutioning: Understand public sector AI strategies and specific agency challenges (e.g., benefits administration backlogs, procurement bottlenecks, public safety resource allocation, or permitting delays). As a Celonis product and government domain expert, find the best problem-solution fit and translate agency requirements into innovative solutions that deliver measurable public impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle within the public sector. Lead technical discovery and capability demonstrations during the complex government pre-sales and procurement (RFP) cycles, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully met.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex legacy processes. Leverage cutting-edge AI technologies to rapidly build creative prototypes in agency hackathons, solving critical pain points to improve constituent experiences.

• Agentic Process Transformation: Support our government customers in achieving real value out of AI deployments at scale, enabling a fundamental shift from traditional, rigid, paper-heavy workflows to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent case triaging or automated compliance checks).

• Proof Projects: End-to-end execution of critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with government enterprise data, identity protocols, and stringent compliance/security frameworks (e.g., StateRAMP, HIPAA, CJIS).

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the State & Local Government vertical, scaling knowledge across the organization regarding agency processes and public sector nuances.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Public Sector (State & Local Government). This includes navigating government procurement cycles, building compelling ROI business cases for public funds, and guiding technical implementations through to constituent value realization.

• Deep understanding of business processes native to state and local governments (such as Health & Human Services, Procurement, Finance, DMV operations, or Public Safety) with the ability to translate high-level policy or agency needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent constituent-facing chatbots, automated processing of policy documents, or grant application analysis).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.

• Strong presentation skills to both internal and external stakeholders (including elected officials, agency directors, and IT leadership), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly scrutinized public sector environments.

• Experience in deploying and monitoring models at scale within government-compliant cloud environments (e.g., AWS GovCloud, Azure Government).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.

Visa sponsorship is not offered for this role.
Learn More about Value Engineering at Celonis Here

Role Description

• As an Applied AI Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks. With Celonis’ Process Intelligence (PI) platform we feed operational context to AI so it understands our customers’ business and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to Executives and ensure successful implementation, adoption and value realization in order to increase the footprint of Celonis at those customers.

Key Responsibilities:

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
• Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
• Proof projects: End-to-end execution of business-critical Proof-of-Value projects, incl. architecture and deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks.
• Ensure Successful Project Outcome: Applied AI Engineers stay involved with projects until agreed value & adoption thresholds are reached
• Specialize in Domains or Industries: To scale knowledge across the organization Applied AI Engineers specialize in domains (e.g. supply chain) and industries

Requirements:

• 7+ years of experience leading technical pre-sales, including defining AI roadmaps, building compelling ROI/TCO business cases and prototyping of machine learning and generative AI solutions.
• Understanding of generative AI techniques like RAG, few shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
• Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
• Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos.
• Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex)

Summary

We are looking for a software engineer to build internal tools that help our battery algorithm team work faster and smarter. You will develop applications for test data analysis, visualization, and documentation, incorporating AI powered capabilities where they accelerate engineering workflows. This is a software engineering role: you will write clean, maintainable code, build intuitive interfaces, and integrate modern AI services into practical tools that engineers actually use.

What You Will Do

• Build Python based applications for analyzing and visualizing large scale battery test data, including time series datasets.
• Develop web based GUIs that let engineers explore, filter, and interact with test results.
• Integrate LLM APIs (e.g., OpenAI, Anthropic) into workflows to automate documentation, extract context from requirement sheets, change reports, and code repositories.
• Create data pipelines that pull from multimodal sources and present actionable insights.
• Collaborate with algorithm engineers and test engineers to understand their pain points and build tools that solve real problems.
• Continuously improve tooling based on user feedback and evolving team needs.

Minimum Qualifications

• B.Sc. or M.Sc. in Computer Science, Electrical Engineering, Mechanical Engineering, or related field.
• 3+ years of professional software development in Python, including data analysis and visualization libraries (pandas, matplotlib, plotly, etc.)
• Experience building web based tools or applications with a frontend component (e.g., React, Streamlit, Dash, or similar)
• Strong debugging and problem solving skills.
• Comfortable working with APIs and integrating third party services.

Preferred Qualifications

• Experience integrating LLM APIs or AI services into applications (prompt engineering, API orchestration, retrieval augmented generation)
• Familiarity with time series data analysis
• Experience with document automation or generation (Word, PDF, slides)
• Exposure to battery management systems or embedded systems workflows• Experience with CI/CD, version control best practices, and collaborative development environments

At.Monks, we believe in fostering an environment where a diversity of perspectives can thrive. We proactively work to design hiring processes that promote equity and inclusion while mitigating bias. We celebrate diversity and are committed to building a team that reflects the communities we serve. We welcome and encourage qualified applicants, from all backgrounds, who are excited to contribute to our mission.  

What We Offer

.Monks has provided a compensation range that represents its good faith estimate of what Media.Monks may pay for the position at the time of posting. .Monks may ultimately pay more or less than the posted compensation range. The salary offered to the selected candidate will be determined based on job-related factors, but not based on a candidate’s sex or any other protected status.

Cupertino, CA

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Senior Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Evaluating ads integrity: understanding changes and drivers of our complex systems, diagnosing fraud claims and mitigating fraud escalations through a set of input/output metrics of each component.
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Economics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Staff Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

• This leader will own the multi-year strategy, roadmap, and execution across the ads supply ecosystem:
  • Supply Exchange & Inventory Integrations: Drive Moloco’s OpenRTB integrations with top-tier third-party supply partners and exchanges, expanding Moloco’s access to high-quality, global, multi-format inventory across gaming and non-gaming verticals.
  • Lead Moloco’s end-to-end General Supply strategy, including Exchange integrations, OpenRTB supply diversification, publisher onboarding, and supply ecosystem expansion.
  • Define, evangelize, and deliver a multi-year supply vision that improves supply quality, scalability, integration reliability, and long-term differentiation
• Conducting deep-dive analysis and experiments to influence product decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Preferred Qualifications:

• Advanced degree. PhD is highly desirable. 
• Deep expertise in the programmatic supply ecosystem, including ad exchanges, SSPs, OpenRTB protocols, auction mechanics, and cross-platform integration
• Demonstrated ability to drive cross-org alignment, influence senior stakeholders (Directors/VPs), and execute through large engineering teams
• Familiarity with publisher ad servers, targeting logic, and impression delivery workflows
• Deep knowledge of supply-side performance metrics such as fill rate, eCPM, latency, bid density, impression opportunities, and unique users—and how to optimize for them
• Hands-on experience with integrations and partner-facing APIs, including defining requirements for interoperability with DSPs, exchanges, ad networks, DMPs, and other adtech partners

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Data Scientist II, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, ML) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers
• Evaluating ads system health: understanding changes and drivers of our complex systems, and diagnosing issues through a set of input/output metrics of each component.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Provide strategic thought partnership to cross-functional teams, leveraging data-driven insights to influence and guide product decisions, roadmap prioritization, and overall business strategy.
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with Product Management, Engineering stakeholders ;work effectively with cross-functional partners in a global company.
• 3+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.
• Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

Location

Palo Alto, CA

Job Description

Rhombus’ Data Engineers are instrumental in designing and implementing data engineering activities on topical, mission-driven projects that inform our national security agenda. They analyze, build, and maintain our organization’s data infrastructure and processing systems. 

Additionally, our Data Engineers perform various code development and query needs for integration with new and existing applications, dashboards and machine learning pipelines. Our Data Engineers work cross functionally with other departments to meet business needs. They utilize their skills at all stages of the analytics pipeline to create results that drive business values and customer success.

Responsibilities:

• Develop code using various programming and scripting languages to automate data ingestion and improve data management processes.
• Architect data repositories, stand up data platforms and develop data pipelines for ingestion, transformation, and aggregation.
• Review existing architecture, data strategy, and improve processes for data governance, data quality, and metadata management.
• Extract and analyze raw data from multiple data sources via APIs, SQL Stored Procedures, or Python scripts.
• Ability to develop scripts and programs for converting various types of data into usable formats and support project team to scale, monitor and operate data platforms.
• Collaborate with a multi-disciplinary team of analysts, data scientists, data engineers, developers, and data consumers in a fast-paced, agile environment.
• You’ll use your experience in analytical exploration and data examination while you manage the assessment, design, building, and maintenance of scalable platforms for clients.
• Communicate project status and results to various levels of leadership.

Qualifications:

• At minimum Bachelor’s degree in Data Analytics, Computer Science, Computer Engineering, Information Systems/Sciences, or other relevant area (or equivalent experience) and at least 3 years of professional experience, or a Master’s degree with strong academic project experience and one year of work experience.  
• Experience with 1 or more programming and scripting languages, with a strong focus on Python, Pandas and Numpy. Other languages include: Shell, PERL, Java, C/C++/C#, Scala, etc.
• Experience with 1 or more of the following relational, noSQL and/or file based storage (e.g. MYSQL, MongoDB, SQL Server, Oracle, Postgres, Hbase, DynamoDB, etc.)
• Experience building and maintaining ETL data pipelines
• Experience with software development life cycle including testing, documenting, delivery and support
• Working knowledge of AWS/cloud technologies
• Experience using query optimization as well as data modeling techniques.
• Familiarity with machine learning frameworks (such as TensorFlow, Scikit-Learn, etc.)

Personal Qualities:

• Bias for action: Rhombus seeks ‘doers’ who will get things done with accuracy, speed and at scale.
• Ability to contextualize data as it relates to Rhombus’ vision. We want someone who can understand the “why” and “so what”, and not just the “how”. Our Data Engineers help us transmit the enthusiasm we have around the data work to the individuals doing that work.
• Must have strong problem-solving skills and demonstrated excellent oral and written communication skills.
• We’re seeking folks with strong intellectual curiosity and creativity, with an ability and willingness to learn new skills and apply novel solutions to problems.
• Comfort in a fast-paced start-up environment is crucial, with the ability to consistently revise your approach in response to new information, and to be flexible and adaptive.

Salary Range

• The estimated base salary range for this position is $110,000 to $180,000/year

Benefits 

• Full medical, dental, vision coverage for employee and dependents 
• 401k matching program 
• PTO and Holidays 
• Bonus and other incentive programs
• Access to mental health program
• Access to Flexible Spending Accounts for Health Care, Dependent and Commuter

About Rhombus 

Rhombus Power Inc. (Rhombus) is a startup located in the heart of Silicon Valley at Stanford Research Park in Palo Alto.  We use cutting-edge cross-disciplinary approaches to solve pressing Big Data and Sensing problems in security, energy, and healthcare. Our advisory board includes two Nobel Laureates and a Draper Prize winner. 

Rhombus compensates, motivates, and develops employees, who are trusted, empowered, and involved. Employees have clear roles and expectations – and their roles are flexible enough to move at the speed of innovation in order to meet and exceed client expectations. We have a unique culture of global purpose, rooted in the innovation and progress of Silicon Valley. 

Rhombus knows that diversity is a condition for success. We are committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action Employer. 

As a Sr. Solutions Architect at Databricks within the Field Engineering org, you will partner with our customers to design scalable data architectures using Databricks technology and services. You have technical depth and business knowledge, and can drive complex technology discussions that express the value of the Databricks platform throughout the sales lifecycle. In partnership with our Account Executives, you will engage with our customers' technical leads, including architects, engineers, and operations teams, with the goal of establishing yourself as a trusted advisor to achieve tangible outcomes. You will work with teams across Databricks and our executive leadership to represent your customers' needs, build valuable customer engagements, and report to the Field Engineering Manager.

The impact you will have:

• You will work with Sales and other essential partners to develop account strategies for your assigned accounts to grow their usage of the platform.
• Establish the Databricks Lakehouse architecture as the standard data architecture for customers through excellent technical account planning.
• You will build and present reference architectures and demo applications for prospects to help them understand how Databricks can be used to achieve their goals to land new users and use cases.
• Capture the technical win by consulting on big data architectures, data engineering pipelines, and data science/machine learning projects; prove out the Databricks technology for strategic customer projects; and validate integrations with cloud services and other 3rd party applications.
• Become an expert in and promote Databricks-inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars.

What we look for:

• 8+ years in a customer-facing pre-sales or consulting role with expertise in at least one of the following technologies:
• Big data engineering (Ex: Spark, Hadoop, Kafka)
• Data Warehousing & ETL (Ex: SQL, OLTP/OLAP/DSS)
• Data Science and Machine Learning (Ex: pandas, scikit-learn, HPO)
• Data Applications (Ex: Logs Analysis, Threat Detection, Real-time Systems Monitoring, Risk Analysis and more)
• Experience translating a customer's business needs to technology solutions, including establishing buy-in with essential customer stakeholders at all levels of the business.
• Experienced at designing, architecting, and presenting data systems for customers and managing the delivery of production solutions of those data architectures.
• Fluent in SQL and database technology.
• Debug and development experience in at least one of the following languages: Python, Scala, Java, or R.
• [Desired] Built solutions with public cloud providers such as AWS, Azure, or GCP
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Travel to customers in your region up to 30% of the time.

THE COMPANY:

Juul Labs's mission is to transition the world’s billion adult smokers away from combustible cigarettes, eliminate their use, and combat underage usage of our products. We have the opportunity to address one of the world’s most intractable challenges through a commitment to exceptional quality, research, design, and innovation. Backed by leading technology investors, we are committed to the same excellence when it comes to hiring great talent.

We are a diverse team that is united by this common purpose and we are hiring the world’s best engineers, scientists, designers, product managers, operations experts, and customer service and business professionals. If the opportunity to build your career is compelling, read on for more details.

ROLE AND RESPONSIBILITIES:

The Mechatronics Engineer is a hands-on role that will be responsible for designing new products that are innovative, cost efficient, reliable, and ship on schedule. This role will drive the validation of concepts via early analysis, prototyping and testing, and work with cross-functional teams to ensure that product requirements are managed to achieve optimal experiences for our customers. In addition, the Mechatronics Engineer will work closely with internal and external partners to technically define designs and ensure that all product and project requirements are met. You will troubleshoot and make improvements to existing products and new products as well as test instrumentation. You will  work closely with other members of the engineering staff to create optimal solutions to a myriad of product related topics such as but not limited to mechanical design, thermal, and data analytics. You will be comfortable sketching and prototyping new ideas and be familiar with engineering best practices, concepts and procedures. We are looking for someone who is flexible and can respond quickly, energetically, and enthusiastically to changes. The person in this role should be a strong communicator who is able to lead effectively and work effectively with peers and management alike in a high-paced global environment. 

• Experienced with embedded control systems and adept at deriving meaningful insights through data analytics to drive improvements in existing algorithms.
• Leverage existing tools, systems, and/or processes for data collection and analysis.
• Takes initiative and ownership of high level work. Negotiates and drives alignment with product architects, managers, and other key stakeholders across multiple disciplines.
• Design, implement, and drive to completion complex system DoEs spanning several engineering disciplines including EE, ME, FW, and SW. 

PERSONAL AND PROFESSIONAL QUALIFICATIONS: 

• Min 2 years working experience in Python and C++ software development, including system design, data structures & algorithms.
• Experienced with Python and Jupyter Notebooks; specifically, numpy, pandas, scipy, and sklearn.
• Prototyping background: Have a maker mentality that allows you to prototype quickly while also producing robust systems that sustain through heavy use and have well-documented construction and troubleshooting guidelines
• 3-5 years of relevant engineering experience in one or more of the following areas: product design, new product release, test engineering.
• Conduct rapid feasibility studies to design for mechanical, fluidic, and thermal robustness.
• Experienced in developing and testing both software applications and mechanical systems, ensuring they work together.
• Oversee internal and external prototyping.
• Work directly with our CM or prototyping partners in support of system assembly build activities.
• Expertise in one (or more of) the areas of: Statistical Analysis, Design of Experiments, Thermal Design, etc.
• Expertise in 3D MCAD, Solidworks preferred.

EDUCATION 

The ideal candidate will possess a Bachelor's degree or higher in Mechatronics, Mechanical Engineering, or a related field

JUUL LABS PERKS & BENEFITS:

• A place to grow your career. We’ll help you set big goals - and exceed them
• People. Work with talented, committed and supportive teammates
• Equity and performance bonuses. Every employee is a stakeholder in our success
• Cell phone subsidy, commuter benefits and discounts on JUUL products
• Excellent medical, dental and vision, disability, and life insurance, plus family support, wellness, legal, and employee assistance program benefits
• 401(k) plan with company matching
• Plus biannual discretionary performance bonuses

Juul Labs is proud to be an equal opportunity employer and is committed to creating a diverse and inclusive work environment for all employees and job applicants, without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. We will consider for employment qualified applicants with arrest and conviction records, pursuant to the San Francisco Fair Chance Ordinance. Juul Labs also complies with the employment eligibility verification requirements of the Immigration and Nationality Act. All applicants must have authorization to work for Juul Labs in the US.

PsiQuantum’s mission is to build the first useful quantum computers—machines capable of delivering the breakthroughs the field has long promised. Since our founding in 2016, our singular focus has been to build and deploy million-qubit, fault-tolerant quantum systems. 

Quantum computers harness the laws of quantum mechanics to solve problems that even the most advanced supercomputers or AI systems will never reach. Their impact will span energy, pharmaceuticals, finance, agriculture, transportation, materials, and other foundational industries. 

Our architecture and approach is based on silicon photonics. By leveraging the advanced semiconductor manufacturing industry—including partners like GlobalFoundries—we use the same high-volume processes that already produce billions of chips for telecom and consumer electronics. Photonics offers natural advantages for scale: photons don’t feel heat, are immune to electromagnetic interference, and integrate with existing cryogenic cooling and standard fiber-optic infrastructure. 

In 2024, PsiQuantum announced government-funded projects to support the build-out of our first utility-scale quantum computers in Brisbane, Australia, and Chicago, Illinois. These initiatives reflect a growing recognition that quantum computing will be strategically and economically defining—and that now is the time to scale. 

PsiQuantum also develops the algorithms and software needed to make these systems commercially valuable. Our application, software, and industry teams work directly with leading Fortune 500 companies—including Lockheed Martin, Mercedes-Benz, Boehringer Ingelheim, and Mitsubishi Chemical—to prepare quantum solutions for real-world impact. 

Quantum computing is not an extension of classical computing. It represents a fundamental shift—and a path to mastering challenges that cannot be solved any other way. The potential is enormous, and we have a clear path to make it real. 

Come join us. 

Job Summary:

As a Data Software Engineer, you will be at the forefront of supporting our data infrastructure and shaping our data systems and processes. You will gather and analyze user and system requirements, create and optimize system models, and develop robust data integration solutions. Through engagement with cross-functional teams, you will refine, test, and develop data solutions to meet complex business needs. You will have an impact on our data systems, driving innovation and efficiency in our data integration processes and our reporting capabilities. Your work will enhance our ability to leverage data for strategic decision-making and operational excellence. 

Responsibilities:

• Extend database models, front-end frameworks, and REST APIs for data system integration and application performance.
• Develop and maintain robust query pipelines for accurate and timely data processing from various sources.
• Support, enhance, and troubleshoot existing data integration systems and reporting infrastructure.
• Write clean, efficient, and well-documented code.
• Collaborate with cross-functional teams to design, develop, and deploy new features.
• Conduct root cause analysis, code reviews, and unit testing in partnership with experienced team members.
• Assist fellow engineers and managers with data queries, development of data processing algorithms, feature enhancements, bug issues, and application navigation.
• Provide comprehensive support and timely resolution for internal customer issues.
• Demonstrate strong problem-solving and decision-making skills with sound judgment.  

Experience/Qualifications:

• Bachelor’s degree in computer science, Math, Physics, Engineering, or related field.
• 3+ years of professional experience in Software Engineering, with a focus on developing and maintaining scalable applications.
• Knowledge of Python and SQL programming languages and integrations.
• Proficiency in data modeling and database design principles.
• Experience designing data-intensive applications using Python frameworks such as Flask, Django, FastAPI, etc.
• Experience with data visualization tools such as: Tableau, PowerBI, Python Dash, or JMP.
• Competency in web application programming and markup languages including JavaScript, HTML, CSS, and related frameworks.
• Practical experience using Git for version control and collaborative software development.
• Proficiency with software development best practices including design, documenting, testing, and debugging.
• Experience with ETL and data ingestion processes and pipelines. 

Preferred Skills & Experience: 

• Familiarity with semiconductor testing and design principles or prior experience in designing data-driven applications in semiconductor industries.
• Experience with data manipulation and scientific computing Python tools and packages, including but not limited to Pandas, NumPy, SciPy, Matplotlib, Jupyter, etc.
• Experience in designing CI/CD pipelines and orchestrating automated deployments. 

Note: PsiQuantum will only reach out to you using an official PsiQuantum email address and will never ask you for bank account information as part of the interview process. Please report any suspicious activity to recruiting@psiquantum.com.

We are not accepting unsolicited resumes from employment agencies.

CSQ127R67

PLEASE NOTE:
Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply.

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our federal government customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems.
• Own production rollouts of consumer and internally facing GenAI applications.
• Serve as a trusted technical advisor to customers across a variety of domains.
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally.
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap.

What we look for:

• Experience working with U.S. federal civilian, state, or local agencies. 
• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy.
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations.
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.).
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
• Passion for collaboration, life-long learning, and driving business value through AI.
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets.

What You'll Do

You will be at the center of informing Zipline on the critical environmental conditions that our aircraft must fly in to achieve business goals, whilst owning the automated system that enforces those limits operationally to ensure flight safety and protecting an excellent and informed customer experience.  You will lead the team that counts the following among its core deliverables:

• Design and develop our automated weather monitoring systems to make real-time go/no-go decisions for missions, as well as forecast in-coming weather conditions that would require pausing deliveries; 
• Define the requirements on flyable weather conditions to achieve business performance goals that are achievable in the context of automated risk system performance;
• Set the pace on simulation- and real-world-based weather-related validation strategies, including performance of the weather system risk decisions, operations simulations to determine the role of the weather system on customer experience dynamics, and developing representative but tractable weather models in Zipline’s high fidelity flight simulation tools;
• Enable and maintain strong and unambiguous communication with customer, fulfilment and flight operations teams, setting expectations for the system uptime, on both seasonal and daily timescales
• Drive the development of ground- and air-based sensing to support the risk posture calculations in a scalable and cost-effective way

What You'll Bring

This is a leadership role on a team that is core to Zipline’s success, and is therefore not an entry level position. Success in this role will require a disciplined and first-principles approach, with a deep connection and understanding at the system and product levels.  You’ll be naturally curious and able to work seamlessly with individuals and teams both inside and outside of your core engineering / scientific discipline, as well as regulatory, operations and business partners.  Experience in many of the following areas are critical to your ability to contribute at the right level:

• You will have a minimum of 5+ years of industry experience, and either be a proven people leader or clearly ready to own and develop a small team (3-5 direct reports).
• Advanced proficiency with scientific python and libraries commonly used for data analysis, e.g., Pandas, Numpy, Scipy, and Matplotlib, XArray, NETCDF.  In addition, you’ll be able to learn new languages and libraries for use in daily work (eg. Rust, C++), and ideally have cloud-native experience with Kubernetes and/or AWS.
• Familiarity with geospatial and meteorological datasets, formats, and tools; in particular you’ll understand how to efficiently process large datasets across distributed systems and ideally have experience with kafka or other streaming data systems
• As well as a strong understanding of descriptive statistics, probability and linear algebra, you will have mastered a wide range of machine learning and statistical techniques, and developed an intuition for what tool to apply in every situation
• Adept at summarizing large datasets visually that make complex results understandable at a glance to different audiences.  You will be able to find creative ways to take the uncertainty of weather prediction and turn it into certainty for the business.
• Excellent understanding of meteorology and climatology, and an ability to communicate the underlying physics and their challenges to a broad audience
• You’ll be highly self-directed; able to drive a roadmap and ruthlessly prioritize, balancing a core roadmap against the emerging needs of a fast-scaling and complex system.  You’ll also be proven in setting the pace of a small team, striving to continuously improve the development tools and processes and help folks around you work smarter
• Experience with aircraft flight and aviation weather and regulation would be helpful, although you will work closely with other leaders of our flight sciences teams so a willingness to learn this rapidly will suffice.  An ability to manipulate the weather would be advantageous, but is not essential.

What Else You Need to Know  

This role is based out of our South San Francisco HQ with minimum of 5 days per week in office. Must be eligible to work in the US and travel globally as needed

The starting cash range for this role is $235,000 to $255,000. Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.

Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, ancestry, national origin, religion or religious creed, mental or physical disability, medical condition, genetic information, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity, gender expression, age, marital status, military or veteran status, citizenship, or other characteristics protected by state, federal or local law or our other policies.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

As a Hunter Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Work directly with prospective, greenfield, customers on their 0 to 1 journey with Databricks 
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems at scale 
• Comfortable programming in, and debugging, Python and SQL
• Experience using agentic coding harnesses and demonstrable experience scaling your work leveraging them 
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

The Opportunity:

We are seeking a Principal Machine Learning Scientist to lead the development of advanced machine learning approaches that accelerate small-molecule drug discovery. This role sits at the intersection of data science, chemistry, and biology, transforming complex scientific datasets into predictive models that guide target discovery, compound design, and translational hypotheses.

Working closely with experimental scientists, the Principal ML Scientist will develop cutting-edge modeling approaches that integrate chemical, biological, and phenotypic data. The successful candidate will play a key role in advancing a data-driven discovery strategy by designing predictive models, deploying innovative algorithms, and translating insights into actionable decisions that improve the speed and success of the discovery of medicines for patients with RAS-driven cancers.

Key responsibilities include:

Scientific Leadership:

• Define and lead machine learning strategies that accelerate early-stage drug discovery.

• Identify opportunities where AI and advanced analytics can meaningfully improve scientific decision-making.

• Drive the adoption of innovative modeling approaches within multidisciplinary discovery teams.

Model Development:

• Develop predictive models for:

  • Compound activity, selectivity, ADME/Tox, and developability properties.

  • Target engagement, mechanism-of-action, and phenotypic datasets.

Apply modern ML techniques such as:

• Graph neural networks.

• Deep learning for molecular representation.

• Generative chemistry models.

• Active learning frameworks for experimental design.

Cross-Functional Collaboration:

• Partner with medicinal chemists to guide compound design and optimization.

• Work with biologists to interpret complex experimental datasets and generate mechanistic hypotheses.

• Collaborate with data scientists and engineers and ML engineers to deploy models into scalable discovery workflows.

Data Integration:

• Integrate heterogeneous datasets including:

• Chemical structure and screening data.

• Imaging and phenotypic screening data.

• Structural biology and molecular simulation outputs.

Required Skills, Experience and Education:

• PhD in machine learning, computational chemistry, computational biology, computer science, or a related quantitative discipline.

• 8+ years experience applying machine learning or advanced analytics to scientific problems.

• Demonstrated experience working with chemical or biological datasets in drug discovery or related domains.

• Strong expertise in:

  • Python-based ML ecosystems (PyTorch, TensorFlow, scikit-learn).

  • Data analysis and scientific computing (NumPy, Pandas).

  • Deep learning and representation learning techniques.

• Strong understanding of early-stage drug discovery workflows.

• Ability to translate biological or chemical questions into computational frameworks and predictive models.

• Proven ability to communicate complex computational insights to.

• Passion for scientific innovation and a relentless commitment to improving patient outcomes.

Preferred Skills:

• Proven track record of applying advanced AI/ML approaches (deep learning, generative modeling, structure-based ML) to drug discovery or related life sciences domains.

• Experience with cheminformatics or bioinformatics toolkits is highly desirable.

• Familiarity with cloud computing and scalable ML workflows is a plus

• Ability to work at the interface of computational and experimental science. 

  #LI-Hybrid  #LI-LN1

The Opportunity:

We are seeking a Senior Machine Learning Scientist to help accelerate drug discovery through advanced analytics and artificial intelligence. This role will develop predictive models and analytical methods that transform complex biological and chemical datasets into actionable insights that guide research decisions.

The Senior Machine Learning Scientist will work at the interface of data science, chemistry, and biology to support target discovery, compound optimization, and translational research. This position requires both strong machine learning expertise and the ability to collaborate effectively with experimental scientists to solve real-world scientific problems.

The successful candidate will contribute to building a data-driven discovery ecosystem where data, analytics, and experimentation continuously inform and accelerate one another.

Key responsibilities include:

Develop Predictive Models for Drug Discovery

• Design and implement machine learning models to predict compound activity, selectivity, and developability.

• Develop predictive frameworks for ADME/Tox, target engagement, and phenotypic screening outcomes.

• Apply advanced modeling approaches including deep learning, graph neural networks, and ensemble methods.

• Evaluate model performance and apply appropriate validation strategies.

• Work with data engineers and ML engineers to integrate models into discovery pipelines.

Analyze Complex Scientific Data

• Perform exploratory data analysis on chemical, biological, and phenotypic datasets.

• Integrate heterogeneous datasets including:

• Chemical structure and screening data.

• High-content imaging data.

• Structural biology and molecular simulation outputs.

• Identify patterns and relationships that inform scientific hypotheses.

Collaborate with Research Scientists

• Partner with medicinal chemists to support compound design and lead optimization.

• Work with biologists to interpret experimental results and identify new target opportunities.

• Translate scientific questions into computational modeling strategies.

Required Skills, Experience and Education:

• PhD in machine learning, computational biology, computational chemistry, computer science, statistics, or a related quantitative field.

• 4–8 years experience applying machine learning or advanced analytics to scientific datasets.

• Python and scientific computing libraries (NumPy, Pandas, SciPy).

• Machine learning frameworks (PyTorch, TensorFlow, scikit-learn).

• Model development, validation, and evaluation methods.

• Data visualization and exploratory analysis.

• Experience working with noisy and incomplete experimental datasets.

Preferred Skills:

• Cheminformatics or molecular modeling tools (RDKit, OpenEye, etc.).

• Multi-omics data analysis.

• Cloud computing environments.

• MLOps or scalable model deployment. 

  #LI-Hybrid  #LI-LN1

As a Data Scientist supporting AI engineers, you will partner with one or more engineering teams, developing actionable insights that guide improvements to the Wayve AI Driver. Using experimental and observational analyses of real and simulated driving, you will help teams advance the functionality, safety, and performance of the Wayve AI Driver, helping to advance Wayve as the leader in end-to-end AI for autonomous mobility.

This means you might:

• Formulate and iterate upon the performance metrics that organize our engineering efforts and guide progress toward commercial success
• Design experiments and targeted off-road measurements to ensure that we deliver product requirements to customers while maintaining safety and performance
• Investigate factors in model training and inference leading to bottlenecks in functionality and performance, identifying and validating hypotheses for unlocking improvements

What we are looking for in our candidate

Essential

• 3+ years experience working in a Data Science role.
• Fluent in querying and building large datasets, writing production-level SQL for use in data-transformation pipelines.
• Prior experience designing robust real-world experiments (e.g. A/B) and critically evaluating test-statistics
• Foundations in the fundamentals behind statistics: testing appropriate distributions, testing the assumptions behind frequentist stats
• Proficient in using a statistical scripting language and data science/ML packages (e.g. python such as pandas, sklearn, statsmodels, scipy or R such as dplyr, caret, stats)
• Well-versed in summarising, visualising and communicating findings in an accessible and compelling way
• Track record of influencing team direction through your findings  
• A bias towards deriving actionable insight that can be used to drive prioritisation and strategy for others.
• Comfortable working asynchronously across time zones with cross-functional partners
• You are deeply curious about building something new and relish the idea of helping to define AV2.0 and how we build it.

Desired

• Practical experience with machine learning (e.g. pytorch). Passion to take research ideas to production.
• Track record of promoting statistical rigour and experimental best practices in your prior roles.
• Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing.
• Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)
• Experience working in a fast-moving tech company or startup.

Role Description

As a Senior Value Engineer specializing in the Public Sector, you are pushing the envelope in solving critical operational challenges for State and Local Government agencies. You will be working with our most strategic public sector clients, understanding their unique objectives—from enhancing citizen services and modernizing legacy systems to optimizing grant management and regulatory compliance—and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with top AI and ML technology partners, such as Microsoft, OpenAI, and Databricks.

With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands the complex realities of government operations (breaking down agency silos) and enables agencies to industrialize AI. This unlocks real ROI on AI deployments, maximizing taxpayer value at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to government CIOs and Agency Directors, and ensure successful implementation, adoption, and value realization to increase the footprint of Celonis across state and local governments.

Key Responsibilities:

• AI Discovery & Solutioning: Understand public sector AI strategies and specific agency challenges (e.g., benefits administration backlogs, procurement bottlenecks, public safety resource allocation, or permitting delays). As a Celonis product and government domain expert, find the best problem-solution fit and translate agency requirements into innovative solutions that deliver measurable public impact.

• Pre- and Post-Sales Execution: Actively drive the full customer lifecycle within the public sector. Lead technical discovery and capability demonstrations during the complex government pre-sales and procurement (RFP) cycles, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully met.

• Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex legacy processes. Leverage cutting-edge AI technologies to rapidly build creative prototypes in agency hackathons, solving critical pain points to improve constituent experiences.

• Agentic Process Transformation: Support our government customers in achieving real value out of AI deployments at scale, enabling a fundamental shift from traditional, rigid, paper-heavy workflows to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent case triaging or automated compliance checks).

• Proof Projects: End-to-end execution of critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with government enterprise data, identity protocols, and stringent compliance/security frameworks (e.g., StateRAMP, HIPAA, CJIS).

• Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the State & Local Government vertical, scaling knowledge across the organization regarding agency processes and public sector nuances.

Requirements:

• 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Public Sector (State & Local Government). This includes navigating government procurement cycles, building compelling ROI business cases for public funds, and guiding technical implementations through to constituent value realization.

• Deep understanding of business processes native to state and local governments (such as Health & Human Services, Procurement, Finance, DMV operations, or Public Safety) with the ability to translate high-level policy or agency needs into specific, impactful AI use cases.

• Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases (e.g., intelligent constituent-facing chatbots, automated processing of policy documents, or grant application analysis).

• Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.

• Strong presentation skills to both internal and external stakeholders (including elected officials, agency directors, and IT leadership), whether leading technical whiteboarding sessions or formal readouts and demos.

• Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have (big plus):

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails suited for highly scrutinized public sector environments.

• Experience in deploying and monitoring models at scale within government-compliant cloud environments (e.g., AWS GovCloud, Azure Government).

• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
  
  

Visa sponsorship is not offered for this role.

Learn More about Value Engineering at Celonis Here

We’re seeking an experienced computational scientist to lead the design, development, and operation of the NGS analysis platform that powers Profluent’s gene editing and protein design programs. You’ll work at the intersection of computational biology, software engineering, and experimental biology to build scalable systems that extract clear, actionable insights from large-scale sequencing data.

In this role, you’ll architect core bioinformatics infrastructure, define analytical strategy, and collaborate closely with experimental and ML teams to accelerate design-build-test-learn cycles. You’ll also mentor team members, promote software engineering best practices, and help shape the future of Profluent’s computational biology capabilities.

Responsibilities 

• Lead design and implementation of scalable NGS analysis pipelines supporting gene editing and protein engineering workflows
• Develop clear, intuitive visualizations and reports to communicate sequencing results and biological insights
• Manage cloud-based compute environments and data systems for large-scale datasets
• Partner with biology teams to analyze results, troubleshoot, and optimize experimental design
• Collaborate with machine learning teams to curate data for model training
• Establish best practices for code review, testing, and CI/CD in computational workflows
• Mentor junior scientists and foster a culture of rigor, reproducibility, and innovation

Qualifications

• PhD or MS in Bioinformatics, Computational Biology, Computer Science, or a related quantitative field
• 5+ years of experience analyzing NGS datasets (e.g., amplicon sequencing, high-throughput editing, or screening experiments)
• Strong programming skills in Python (pandas, numpy, biopython, etc.)
• Expertise with workflow orchestration tools (Nextflow, Snakemake) and cloud environments (GCP, AWS)
• Experience with containerization (Docker, Kubernetes) and scalable compute infrastructure
• Deep understanding of Linux, git-based version control, and software engineering best practices
• Proven ability to transform complex sequencing data into actionable biological insights

Preferences (but not required)

• Experience with gene editing technologies (CRISPR, base or prime editing; strongly preferred)
• Familiarity with SQL and data modeling for biological or experimental data
• Experience with LIMS platforms (e.g., Benchling) and lab data integration
• Track record of developing production-quality scientific software or open-source bioinformatics tools

What We Offer

• High-growth opportunity with meaningful impact on the future of protein design
• Competitive compensation package with equity participation
• 401(k) with a strong employer match
• Comprehensive benefits including health/dental/vision insurance
• Generous PTO policy and commitment to work-life balance
• Professional development opportunities in a cutting-edge field at the intersection of AI and biology

Profluent Bio, Inc is an equal opportunity employer promoting diversity and inclusion in the workspace. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical conditions, veteran status, sexual orientation, gender (including gender identity and gender expression), sex (which includes pregnancy, childbirth, and breastfeeding), genetic information, taking or requesting statutorily protected leave, or any other basis protected by law.

Work Authorization Requirement

Applicants must have ongoing work authorization in the United States that does not require employer sponsorship. Sponsorship will not be provided now or at any time in the future for this position.

Employment Eligibility Verification

Legal authorization to work in the United States is required. In compliance with federal law, all persons hired must verify their identity and work eligibility and complete the required employment verification form upon hire.

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE

As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.

Reporting to the Field Engineering Manager, you will collaborate with customer stakeholders, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide one of our largest AI native customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our users
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.

What we look for:

• 7+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
  • Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
  • Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply.  We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

What you’ll do:

• Design, implement, and maintain internal software libraries and applications as well as computing infrastructure to enable engineers to solve problems faster and more efficiently. Promote the use of shared computational infrastructure, tools, and practices across engineering teams within the Flight Sciences department.
• Develop processes and software tools to improve the reproducibility and traceability of computations. Drive the implementation of such tools.
• Promote a culture of software excellence across the engineering organization.
• Understand the needs of various engineering teams to efficiently utilize High-Performance Computing (HPC) resources, and make informed decisions on infrastructure solutions to ensure optimal resource utilization and cost savings.
• Maintain and administer on-premises HPC resources. 
• Advocate for engineering and computing needs with the company-wide IT department.

What you need:

• Master's or Ph.D. in Aerospace Engineering, Mechanical Engineering, Computational Engineering, or a related field.
• 5+ years of experience as a user and developer of scientific/engineering software for flight sciences or similar disciplines (such as aerodynamics, acoustics, control, loads, thermal analysis, mass properties, vehicle simulation, etc.) in a fast-moving environment.
• Demonstrated experience in developing computing software and infrastructure, with proficiency in the scientific Python ecosystem (NumPy, SciPy, Pandas, Scikit-learn, TensorFlow/PyTorch, VTK).
• Demonstrated experience in standard best practices in software development, including version control, CI/CD, software testing, environment management.
• Demonstrated experience with the design and administration of HPC systems, either on-premise or cloud (AWS preferred). Knowledge of Linux administration, high speed network interconnects, parallel file systems, and MPI required.
• Experience with HPC management software (Slurm/PBS/Torque, OpenHPC/Bright, Warewulf/XCat, Spack/EasyBuild, Lmod).
• Good understanding of enterprise IT and common network security practices.
• Excellent problem-solving skills and ability to work collaboratively in a team environment.

Bonus qualifications:

• Experience as an engineer in one or more of the following areas of aircraft design - aerodynamics, conceptual design, rotor/propeller design, vehicle simulation, loads and dynamics, structural design, stress analysis, GNC.
• Contributions to open source scientific software projects.
• Experience with MATLAB and Simulink.
• Proficiency in one or more compiled languages (e.g. C/C++, Fortran, Rust).
• Familiarity with databases (SQL, NoSQL, time-series) and database application design (ORM/ODM).
• Experience with software packaging (Pip, Conda, Spack) and containerization technologies (Docker/Singularity/Shifter) for scientific software.
• Familiarity with software configuration management tools (Chef/Puppet/Ansible).
• Familiarity with common CI/CD tools and practices (TeamCity/Jenkins, Artifactory, Docker, etc.).
• Experience with analysis tools and workflows for aircraft/rotorcraft design (aerodynamics, CFD, GNC, loads, structural analysis, CAD, mass properties, etc.).

At Archer, we aim to attract, retain, and motivate talent with the skills and leadership needed to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s strategy. For this position, we are targeting a base pay range of $162,800 - $217,600. Actual compensation offered will be determined by job-related knowledge, skills, and experience.        

Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer’s People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

Our generative models learn the blueprint of life by modeling large-scale evolutionary data, enabling us to engineer and write biology in unprecedented ways. We are seeking a passionate Computational Research Intern to join moonshot projects at the intersection of bioinformatics and machine learning.

This is a rare opportunity to tackle open-ended scientific and engineering challenges with direct potential for high-impact publications and real-world applications in synthetic biology and protein engineering.

Responsibilities

• Design and implement computational approaches to advance cutting-edge research in bioinformatics and machine learning
• Analyze large-scale genomic and protein datasets to uncover new biological insights and capabilities
• Collaborate closely with scientists and engineers across machine learning, protein engineering, and biology teams
• Document and present research findings internally, with the potential to publish in leading journals and conferences

Qualifications 

• Enrolled in a BS, MS, or PhD program in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field
• Strong programming skills in Python and familiarity with scientific computing libraries (e.g., NumPy, pandas, Jupyter)
• Experience in one or more of the following: machine learning, large-scale data analysis, genomics, or protein bioinformatics
• Excellent problem-solving skills, scientific curiosity, and ability to work both independently and collaboratively

Internship Details

• Typical duration: 12 weeks, with flexible start dates
• Hybrid: 2 - 3 days on-site per week in our Emeryville, CA headquarters
• Salary: $1,667 per week
• Opportunity to publish your work and make a lasting impact in computational biology and AI-driven protein design

What We Offer

• Work on moonshot projects at the frontier of AI and biology
• Mentorship from leading experts in bioinformatics, machine learning, and synthetic biology
• A dynamic, mission-driven environment with the resources of a fast-growing, well-funded startup
• Competitive internship compensation and benefits

Heartflow is a medical technology company advancing the diagnosis and management of coronary artery disease using cutting-edge technology. As we continue to revolutionize precision heartcare through our AI-driven integrated heart care solutions , we are seeking a proactive, self-starting Senior Data Engineer - AI Empowerment. This role is focused on architecting the infrastructure necessary to empower business processes with AI, specifically leveraging the power of our data lake to fuel advanced models.

Role Overview

In this role, you will move beyond simple ETL to building robust, observable data products that serve as the foundation for AI enablement. You will architect data pipelines that integrate with Google Vertex AI and Claude to automate complex business workflows. You will act as a technical lead, balancing high-level AWS infrastructure management with the mission of making our data lake assets "AI-ready" for the entire organization.

Job Responsibilities

• AI Pipeline Orchestration: Build and manage complex data pipelines utilizing the Dagster framework to orchestrate data flows into Google Vertex AI for model training and deployment.
• Stakeholder Engagement: Work closely with stakeholders from requirements gathering to training and ongoing support
• LLM Integration: Design and maintain specialized pipelines that leverage Claude to automate business processes, ensuring high accuracy and context-aware outputs from our data lake.
• AI-Driven Business Enablement: Enable departments to leverage AI-powered insights by providing clean, governed, and structured data sets optimized for LLM consumption.
• Semantic Layer & BI: Support a unified semantic model in Cube (Cube.js) to provide consistent metrics that fuel both AI agents and human-centric dashboards.
• Modern Data Stack Management: Manage and optimize high-performance storage and query layers using Iceberg, Amazon Redshift, and Athena to support the data-intensive needs of AI applications.
• Mentorship & Governance: Lead data governance initiatives to ensure "AI-readiness" and provide technical mentorship to junior engineers on best practices for AI-centric data engineering.
• 24/7 Support: On-call support for 24/7 critical business processes

Skills Needed

• Languages & Libraries: Expert proficiency in Python (specifically pyiceberg, boto3, polars, and pandas) and SQL.
• AI Platforms: Hands-on experience integrating data pipelines with Google Vertex AI and utilizing Claude for natural language processing tasks.
• AWS Ecosystem: Deep hands-on experience with ECS (Fargate/EC2), Redshift, and Athena.
• Pipeline Concepts: Mastery of Dagster data pipeline concepts, including Software-Defined Assets and declarative orchestration.
• Modeling: Strong experience in Cube Dev semantic modeling and building reporting layers for complex business workflows.
• Domain Knowledge: Proven track record in developing data systems that enable AI/ML capabilities or advanced business process automation.

Educational Requirements & Work Experience

• Education: B.S. or M.S. in Computer Science, Data Engineering, or a related field.
• Experience: 5+ years of Data Engineering experience, with significant time spent in AWS environments and a background in enabling AI/ML workflows.
• Leadership: Demonstrated ability as a self-starter with experience mentoring peers and leading technical projects.

A reasonable estimate of the base salary compensation range is $160,000 to $200,000 per year, and bonus. #LI-IB1

We are seeking a proactive, self-starting Senior Data Engineer to architect and scale our data infrastructure, with a specific focus on HRIS, Market Research and Revenue Cycle pipelines, reporting and governance. In this role, you will move beyond simple ETL to building robust, observable data products using Dagster and Cube while ensuring data governance practices and catalog management are consistently maintained. You will act as a technical lead, balancing high-level AWS infrastructure management (ECS, Redshift, Athena) with the mentorship of junior team members to foster a culture of engineering excellence

Job Responsibilities:

• Orchestration & Automation: Build and manage complex data pipelines utilizing the Dagster framework, leveraging AWS ECS for containerized task execution.
• Revenue Cycle Expertise: Design and maintain specialized pipelines and reports for Revenue Cycle Management, ensuring high accuracy for financial data processing.
• Semantic Layer & BI: Support the development of a unified semantic model in Cube (Cube.js) to provide consistent metrics across the organization.
• Modern Data Stack Management: Manage and optimize high-performance data storage and query layers using Iceberg, Amazon Redshift and Athena.
• Mentorship & Governance: Lead data governance initiatives and provide technical mentorship to junior engineers, ensuring adherence to Python and SQL best practices.

Skills Needed:

• Languages & Libraries: Expert proficiency in Python (specifically pyiceberg, boto3, polars, and pandas), SQL, DBT, and YAML.
• AWS Ecosystem: Deep hands-on experience with ECS (Fargate/EC2), Redshift (clustering and optimization), and Athena (serverless querying).
• Pipeline Concepts: Mastery of Dagster data pipeline concepts, including Software-Defined Assets and declarative orchestration.
• Modeling: Strong experience in Cube Dev semantic modeling and building reporting layers for complex financial workflows.
• Domain Knowledge: Proven track record in developing Revenue Cycle pipelines and financial reporting systems.
• Reporting Solution: Experience building and supporting Tableau datasets and reports.

Educational Requirements & Work Experience: 

• Education: B.S. or M.S. in Computer Science, Data Engineering, or a related field.
• Experience: 5+ years of Data Engineering experience, with significant time spent in AWS environments and a strong background in RCM/Financial data.
• Leadership: Demonstrated ability as a self-starter with experience mentoring peers and leading technical projects.

24/7 Support: On-call support for 24/7 critical business processes.

Stakeholder Engagement: Work closely with stakeholders from requirements gathering to training and ongoing support.

A reasonable estimate of the base salary compensation range is $140,000 to $170,000 per year, and bonus. #LI-IB1

Want to help us help others? We’re hiring! 

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

We’re looking for a Data Science Manager to architect and lead the next generation of marketing data science at GoFundMe. This role will build and scale the foundations of applied data science and AI that empower our Marketing, Growth, and Finance teams to make high-confidence, ROI-positive investment decisions. You’ll serve as a player-coach for a talented group of experienced data scientists, driving innovation while ensuring excellence in delivery.

Candidates considered for this role will be located in the San Francisco, Bay Area. There will be an in-office requirement of 3x a week.

The Job

• Build a strong AI and data science foundation: Develop scalable pipelines, reusable modeling frameworks, and robust experimentation platforms to support marketing and growth decision-making.
• Lead end-to-end data science & AI projects: From requirements gathering through feature engineering, modeling, validation, deployment, and monitoring.
• Establish best practices: Champion standards in model governance, reproducibility, data quality, and system reliability to ensure sustainable and trustworthy AI adoption.
• Drive marketing science innovation: Apply advanced methods—causal inference, uplift modeling, multi-touch attribution, and media mix modeling—to unlock insights and optimize spend.
• Advance forecasting & ROI modeling: Deliver budget allocation frameworks and predictive models that guide long-term roadmap planning and marketing efficiency.
• Partner cross-functionally: Work closely with Marketing, Growth, Product, Engineering, and Finance leaders to align analytics initiatives with revenue impact.
• Invest in people: Mentor, coach, and elevate a team of high-performing data scientists; foster a culture of technical rigor, curiosity, and applied innovation.
• Push the frontier of applied AI in marketing: Evaluate emerging generative and predictive AI approaches for audience segmentation, creative optimization, personalization, and campaign efficiency.

You

Experience & Education

• 8+ years of experience in data science roles with direct impact on marketing, growth, or revenue optimization.
• Master’s or Ph.D. in a quantitative field (Statistics, Mathematics, Economics, Computer Science, Physics, Operations Research or related), or equivalent applied experience.

Technical Skills

• Advanced proficiency in Python (NumPy, pandas, scikit-learn) and SQL (window functions, optimization). (Please note, advance python and SQL proficiency will be tested during the interview process for this position.) 
• Deep experience with experimentation frameworks: A/B testing, causal inference, uplift modeling, and attribution models.
• Proven success in forecasting, optimization, and budget allocation models for marketing and growth functions.
• Hands-on with data platforms (Snowflake, Databricks) and BI tools (Looker, Tableau, or equivalent).
• Strong data storytelling and executive presentation abilities.

Leadership & Collaboration

• Exceptional communication skills with the ability to influence executive stakeholders and translate data into actionable business recommendations.
• Experience developing senior data scientists and elevating team practices.
• Demonstrated ability to define a strategic vision for applied data science in marketing, balancing rapid experimentation with long-term infrastructure investments.

Preferred 

• Familiarity with experimentation and web/mobile analytics platforms (Optimizely, GrowthBook, Google Analytics, Amplitude).
• Experience integrating with marketing APIs (Google, Meta, programmatic platforms) for campaign optimization.
• Prior exposure to generative AI or LLMs in marketing use cases (e.g., personalization, targeting, creative analysis).
• Knowledge of multi-arm and contextual bandit algorithms for adaptive experimentation and continuous marketing optimization.
• Familiarity with ML ops practices: version control, model monitoring, scalable ETL frameworks.

Why you’ll love it here

• Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year.
• Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.
• Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together.
• Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits.
• Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
• Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow.
• Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.
• Community Engagement: Make a difference through our volunteering program.

We live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!

GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences.  We do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.

The total annual salary for this full-time position is $202,000 - $303,000 + equity + benefits. The company also offers equity and other benefits to employees, including healthcare, dental, vision, life insurance and 401(k) saving program. In addition to this wage, there are geolocation differentials that will increase pay depending on the work location. Additionally pay may vary depending on other factors including skills, experience, education, or training. Your recruiter can share more about the specific total compensation package based on your location during the hiring process. 

If you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com. 

Global Data Privacy Notice for Job Candidates and Applicants:

Depending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here. By submitting your application, you are agreeing to our use and processing of your data as required. 

Learn more about GoFundMe:

We’re proud to partner with GoFundMe.org, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their FY ‘25 annual report.

Our annual “Year in Help” report reflects our community’s impact in advancing our mission of helping people help each other.

For recent company news and announcements, visit our Newsroom.

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Metaview as part of our hiring process for jobs in NYC and certain features may qualify it as an automated employment decision tool (AEDT), as defined by New York City Local Law 144. As part of the hiring process, we provide Metaview with job requirements and candidate submitted resumes and application materials to assist in evaluating job-related qualifications. While this tool is used to improve efficiency and support our recruiting personnel, all final hiring decisions are made by GoFundMe employees.

We began using Metaview on March 10, 2026. The Metaview tool has been reviewed by an independent auditor. Results of the audit may be viewed here. The tool evaluates your professional experience, technical skills, education, and other qualifications using information collected directly from your submitted resume and application materials; all such data is retained in accordance with GoFundMe’s Personnel Privacy Notice and applicable legal requirements. If you would like to request an alternative selection process or a reasonable accommodation, please contact accommodationrequests@gofundme.com.

Want to help us help others? We’re hiring! 

GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010.

We’re looking for a Staff Data Scientist, Pricing to serve as the senior individual contributor driving the science, strategy, experimentation and AI deployment behind pricing and yield optimization at GoFundMe. This role sits at the intersection of economics, behavioral science, experimentation, and machine learning, with direct responsibility for optimizing donation conversion, donation amounts, and donor experience across the product.

Candidates considered for this role will be located in the San Francisco Bay Area. There will be an in-office requirement of 3x a week.

The Job

• Own donation pricing and amount optimization end-to-end: Define the analytical strategy, modeling frameworks, and success metrics for pricing recommendations across product surfaces, balancing conversion, donation amounts, and long-term donor trust.
• Model human behavior using economics and AI: Apply economic theory, behavioral science, and machine learning to understand donor decision-making, estimate elasticity, and predict responses to changes in product design and choice architecture.
• Leverage non-transactional behavioral signals: Model sparse and indirect signals (e.g., navigation, hesitation, context, device, timing) to detect shifts in intent and interaction patterns beyond observed transactions.
• Build adaptive and reinforcement-aware systems: Design models that learn over time using experimentation signals, feedback loops, and reinforcement concepts (e.g., contextual bandits or sequential decision-making) where appropriate.
• Lead experimentation and causal learning: Partner with Product and Engineering to design robust experimentation and measurement frameworks, ensuring pricing and donation models are causal-aware, interpretable, and safe to deploy at scale.
• Incorporate external data and context: Augment behavioral models with external datasets (macroeconomic indicators, seasonality, regional or temporal signals) to better understand and anticipate donor behavior.
• Translate insights into action: Convert complex economic and behavioral analyses into deployable models, clear product recommendations, and measurable business impact.
• Influence through storytelling and leadership: Communicate insights effectively to senior leaders, humanize donor behavior through narrative, and serve as a trusted thought partner on pricing and donation strategy.
• Raise the technical bar: Set best practices for modeling rigor, validation, monitoring, and iteration; mentor other data scientists and elevate pricing science across the organization.

You

Experience & Education

• Either a Ph.D. in Economics, Applied Economics, or a closely related quantitative field, demonstrating the ability to push the boundaries of applied research and translate theory into practical modeling approaches OR 8+ years of industry experience in data science, applied economics, pricing, marketplace optimization, or monetization at a high-tech digital company, with a proven track record of owning and scaling pricing or decisioning systems.
• Deep experience applying economic reasoning, causal inference, and behavioral modeling to real-world decision-making problems.
• Demonstrated ability to own ambiguous, high-impact problems and deliver measurable business outcomes.

Core Skills

• Strong foundation in econometrics, causal inference, and behavioral modeling.
• Deep understanding of price elasticity, choice modeling, and decision science.
• Experience modeling noisy, sparse, or non-transactional behavioral data.
• Hands-on experience designing and interpreting experiments and causal signals.
• Familiarity with reinforcement learning, bandits, or adaptive optimization concepts (applied or research-driven).

Technical Skills

• Advanced proficiency in Python (pandas, NumPy, scikit-learn, PyMC/Stan or equivalent) and SQL, with the ability to build, validate, and iterate on complex analytical and modeling workflows.
• Demonstrated ability to leverage modern AI tools and coding agents (e.g., LLM-based assistants, autonomous or semi-autonomous coding agents, model-driven feature generation, synthetic data generation) to accelerate research, prototyping, and productionization of models.
• Experience designing or applying LLM-based or AI-assisted solutions to complex decisioning problems (e.g., feature extraction from unstructured data, rapid experimentation, simulation, or model orchestration), beyond basic prompt usage.

Leadership & Collaboration

• Exceptional ability to tell clear, compelling stories from complex data.
• Comfortable influencing product direction and executive decision-making.
• Demonstrated ability to lead without authority and elevate team practices.

Preferred but not required

• Experience in consumer pricing, marketplaces, or digital payments/donations.
• Experience partnering with engineering to productionize models and AI-driven systems, including monitoring, evaluation, and iteration in live environments.
• Familiarity with modern data platforms (Snowflake, Databricks) and experimentation infrastructure; experience with model versioning and validation is a plus.
• Strong data visualization, documentation, and presentation skills, with an emphasis on clarity and executive-ready communication.

Why you’ll love it here

• Make an Impact: Be part of a mission-driven organization making a positive difference in millions of lives every year.
• Innovative Environment: Work with a diverse, passionate, and talented team in a fast-paced, forward-thinking atmosphere.
• Collaborative Team: Join a fun and collaborative team that works hard and celebrates success together.
• Competitive Benefits: Enjoy competitive pay and comprehensive healthcare benefits.
• Holistic Support: Enjoy financial assistance for things like hybrid work, family planning, along with generous parental leave, flexible time-off policies, and mental health and wellness resources to support your overall well-being.
• Growth Opportunities: Participate in learning, development, and recognition programs to help you thrive and grow.
• Commitment to DEI: Contribute to diversity, equity, and inclusion through ongoing initiatives and employee resource groups.
• Community Engagement: Make a difference through our volunteering program.

We live by our core values: impatient to be great, find a way, earn trust every day, fueled by purpose. Be a part of something bigger with us!

GoFundMe is proud to be an equal opportunity employer that actively pursues candidates of diverse backgrounds and experiences.  We do not discriminate on the basis of race, color, religion, ethnicity, nationality or national origin, sex, sexual orientation, gender, gender identity or expression, pregnancy status, marital status, age, medical condition, mental or physical disability, or military or veteran status.

The annual U.S. salary range for this full-time position is $179,500 - $269,500. The company also offers equity and other benefits to employees, including healthcare, dental, vision, life insurance and 401(k) saving program. In addition to this wage, there are geolocation differentials that will increase pay depending on the work location. Additionally pay may vary depending on other factors including skills, experience, education, or training. Your recruiter can share more about the specific total compensation package based on your location during the hiring process.

If you require a reasonable accommodation to complete a job application or a job interview or to otherwise participate in the hiring process, please contact us at accommodationrequests@gofundme.com. 

Global Data Privacy Notice for Job Candidates and Applicants:

Depending on your location, the General Data Protection Regulation (GDPR) or certain US privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available here. By submitting your application, you are agreeing to our use and processing of your data as required. 

Learn more about GoFundMe:

We’re proud to partner with GoFundMe.org, an independent public charity, to extend the reach and impact of our generous community, while helping drive critical social change. You can learn more about GoFundMe.org’s activities and impact in their FY ‘25 annual report.

Our annual “Year in Help” report reflects our community’s impact in advancing our mission of helping people help each other.

For recent company news and announcements, visit our Newsroom.

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Metaview as part of our hiring process for jobs in NYC and certain features may qualify it as an automated employment decision tool (AEDT), as defined by New York City Local Law 144. As part of the hiring process, we provide Metaview with job requirements and candidate submitted resumes and application materials to assist in evaluating job-related qualifications. While this tool is used to improve efficiency and support our recruiting personnel, all final hiring decisions are made by GoFundMe employees.

We began using Metaview on March 10, 2026. The Metaview tool has been reviewed by an independent auditor. Results of the audit may be viewed here. The tool evaluates your professional experience, technical skills, education, and other qualifications using information collected directly from your submitted resume and application materials; all such data is retained in accordance with GoFundMe’s Personnel Privacy Notice and applicable legal requirements. If you would like to request an alternative selection process or a reasonable accommodation, please contact accommodationrequests@gofundme.com.

While candidates in the listed location(s) are encouraged for this role, candidates in other US locations will be considered. #LI-REMOTE

As a Solutions Architect on the Digital Natives team, you will work with the leading data engineering, data science & ML teams in the market to push the boundaries of what big data architectures are capable of. 

Reporting to the Field Engineering Manager, you will collaborate with strategic customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.

We are looking for high technical aptitude individuals with a deep sense of ownership and a desire to help customers ship solutions at production scale. Ideal candidates are deeply curious, capable of operating with confidence in ambiguous situations, and are extremely adaptable. 

The impact you will have:

• You will partner with the sales team and provide technical leadership to help customers understand how Databricks can help solve their business problems.
• Drive technical discovery and solution design, focusing on winning competitive deals and accelerating time-to-value in strategic accounts.
• Continuously research & learn new technologies and their implementations on Databricks
• Consult on Big Data architectures, implement proof of concepts for strategic projects, spanning data engineering, data science and machine learning, and SQL analysis workflows. As well as validating integrations with cloud services, home grown tools, and other 3rd party applications
• Collaborate with your fellow Solutions Architects, using your skills to support each other and our customers
• Become an expert in, promote, and recruit contributors for Databricks inspired open-source projects (Spark, Delta Lake, and MLflow) across the developer community.
• Work closely with account executives to create and execute account penetration strategies, focusing on winning technical decision-makers and building new customer champions.
• Build trusted advisor relationships with senior and executive stakeholders by articulating the business value of Databricks in clear, outcomes-driven terms.
  
  

What we look for:

• 5+ years in a data engineering, data science, technical architecture, or similar pre-sales/consulting role
• Experience building distributed data systems
• Comfortable programming in, and debugging, Python and SQL
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Expertise in one of the following:
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, pytorch, Tensorflow)
• Strong executive presence with the ability to influence C/VP-level stakeholders and align technical solutions to strategic business priorities.
• Available to travel to customers in your region
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• Nice to have: Databricks Certification
  
  

NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.

CSQ127R66

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

• Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems.
• Own production rollouts of consumer and internally facing GenAI applications.
• Serve as a trusted technical advisor to customers across a variety of domains.
• Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally.
• Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap.

What we look for:

• Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy.
• Expertise in deploying production-grade GenAI applications, including evaluation and optimizations.
• Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.).
• Experience building production-grade machine learning deployments on AWS, Azure, or GCP.
• Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience.
• Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike.
• Passion for collaboration, life-long learning, and driving business value through AI.
• [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets.

P-345

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, technical guides, and demo applications for customers
• Provide escalated support for critical customer operational issues
• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 5+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP
• Experience in at least one of the following:
  • Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
  • Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
  • Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
• Nice to have: Databricks Certification

P-344

At Databricks, our customers challenge us with solving some of the world's toughest data problems. Our customers rely on our Solutions Architect team to understand the technologies that power our platform, the broader cloud and technology ecosystems, and how they can all be brought together to solve these problems.

Solutions Architects at Databricks lead the adoption of the Databricks Unified Analytics Platform. As a member of our team, you will sharpen your skills on open-source projects such as Apache Spark™, MLflow, and Delta Lake to advocate the Lakehouse paradigm on public cloud providers. You will gain expertise in cloud platforms, data engineering, data analytics, data science, and machine learning. In this customer-facing role, you will identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through implementations to deliver strategic business value. You will partner with the sales team to build relationships with our customers and establish yourself as a trusted advisor.

Databricks' culture thrives on collaboration and teamwork, and you will contribute your knowledge to our teams by participating in our subject matter expert groups. In this role, you will report to the Solutions Architect Leader supporting the specific business segment.

If you are a technologist interested in Data and AI, and enjoy prototyping solutions for customers, this role is for you.

The impact you will have:

• Provide technical leadership for customers to evaluate and adopt Data and AI solutions from Databricks
• Consult on big data architecture, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present reference architectures, technical guides, and demo applications for customers
• Provide escalated support for critical customer operational issues
• Become an expert in, and evangelize Databricks driven open-source projects (Apache Spark™, Delta Lake, MLflow, Koalas) across developer communities through meetups, conferences, and webinars
• Use your strengths to help your fellow SA's, and drive cross-functional relationships across the company
• Travel to customers (up to 30%, of which 80%+ local to your region)

What we look for:

Solution Architects are customer-facing. You'll need to be comfortable communicating ideas to various audiences through presentations, whiteboarding, architecture discussions, and platform demonstrations.

• 3+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in and debugging at least one of Python, Scala, Java, SQL, or R
• Have built solutions with public cloud providers, such as AWS, Azure, or GCP
• Experience in at least one of the following:
  • Data Engineering technologies (e.g., Spark, Hadoop, Kafka)
  • Data Warehousing (e.g., SQL, OLTP/OLAP/DSS)
  • Data Science and Machine Learning technologies (e.g., pandas, scikit-learn, HPO)
• [Preferred] Degree in a quantitative discipline (e.g., Computer Science, Applied Mathematics, Operations Research, etc.)
• Nice to have: Databricks Certification

COMPANY

Octant is pioneering a new generation of precision medicines by combining synthetic biology, chemistry, and AI/ML to tackle complex cellular mechanisms driving human disease. We are a small molecule therapeutics company scaling drug discovery to unlock therapies for genetically defined and historically intractable diseases.

JOB DESCRIPTION

We're looking for a computational drug discovery intern to join Octant this summer in a program funded by the Gates Foundation to identify small-molecule drugs targeting HPV-driven cancers. In this role, you'll work alongside our computational and experimental teams to build and iterate on machine learning models, explore molecular representations and structure-activity relationships, and help drive compound design and prioritization from data to decision.

THIS INTERNSHIP MIGHT BE GREAT FOR YOU IF YOU ARE/HAVE:

• Currently enrolled in or recently completed a BS or MS in a quantitative field (CS, bioinformatics, applied math, data science, computational biology, or adjacent)
• Proficient in Python for data analysis and scripting (pandas, numpy, scikit-learn at minimum)
• Experience building or training ML models on real datasets, not just coursework exercises
• At least one substantive research experience (academic lab, industry internship, or independent project) where you drove a project from question to result
• Familiarity with version control (git) and working in shared codebases
• Coursework or research exposure in at least one biological science area
• Ability to communicate results to both computational and experimental audiences
• Comfort with ambiguity and fast iteration. The project work is on a weekly cadence, which means making judgment calls with incomplete data, not waiting for perfect information

EVEN BETTER IF YOU HAVE:

• Hands-on experience with molecular representations (SMILES, fingerprints) or cheminformatics toolkits (RDKit, DeepChem)
• Experience with cloud/distributed compute environments (Databricks, Spark, or similar)
• Understanding of structure-activity relationships, compound libraries, or hit expansion concepts
• Demonstrated ability to work across the computational-experimental boundary (e.g., designed an analysis that informed a wet-lab decision, or interpreted assay data to guide a model)
• Familiarity with active learning or Bayesian optimization frameworks
• Experience building or working with agentic systems, LLM tool-use pipelines, or multi-step automated workflows
• Familiarity with prompt engineering and structured output parsing from language models
• Experience with workflow orchestration or pipeline tools (Databricks, Airflow, or similar)
• Comfort designing and consuming APIs or integrating across multiple tools/platforms programmatically
• Experience with software engineering best practices beyond scripting (testing, error handling, logging, modular code design)
• Familiarity with database interactions (SQL, querying structured data stores) in a production or semi-production context

Optional: Along with your application, please share a paper/preprint/software repo that best highlights your strengths so we can better understand the work you've led. If there is nothing public, please summarize that work in a few paragraphs. 

The pay range for this role is $1,400 to $1,500 per week, depending on experience. The duration of the internship is up to 10 weeks.

Octant is located in Emeryville, California and we work onsite.

Octant is an equal opportunity company that values applicants of all backgrounds. We’re committed to fostering an inclusive and supportive work environment. We value less traditional backgrounds, and may consider an equivalent combination of knowledge, skills, education, and experience to meet minimum qualifications. We know that confidence-gap and imposter syndrome can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you.

At our labor marketplace tech company, we believe that even in the age of AI, the core of success comes down to good people doing honest work. We're seeking a curious and driven Product Operations Analyst to help us operationalize our intelligent product features, ensuring they deliver value and efficiency to our users. This is a fantastic opportunity to grow your career at the intersection of product, data, and user experience.

Who You Are:

• An early-career professional, from a recent graduate up to 2 years of experience, looking to build a career in product operations.
• A Passion for Product & Tech: You are fascinated by how technology products are built, launched, and improved. You're eager to learn and contribute to the product lifecycle.
• Curious about AI: You don't need to be an expert, but you're an enthusiast who is interested in learning about the latest AI technologies and tools and their potential to improve user experiences.
• Analytical & Data-Curious: You have a knack for looking at data to find patterns and answer questions. You're comfortable with spreadsheets (Excel/Google Sheets) and are excited to learn more about data analysis.
• A Problem-Solver: You enjoy tackling challenges and are motivated to find efficient solutions. You're organized, detail-oriented, and not afraid to ask questions to get to the root of a problem.
• Eager to Learn Technical Skills: You have an interest in learning data analysis tools. Any exposure to SQL or other data tools is a plus, but a strong desire to learn is most important.
• Collaborative & Hands-On: You are a team player who is ready to roll up your sleeves and help with a variety of tasks, from testing new features to analyzing user feedback.

What You'll Do:

• Support Product Rollouts & Adoption: Work closely with product, design, and operations teams to help execute outreach and rollout plans for new features.
• Contribute to Product Development: Act as a key tester for new product capabilities. You'll document your findings, share user feedback with the product team, and help identify areas for improvement.
• Analyze Feature Performance: Assist in monitoring the performance of new features by tracking key metrics, analyzing user behavior, and summarizing insights for the team.
• Champion the User Experience: Be a voice for our users. You'll help gather, organize, and analyze user feedback from various channels to inform the product roadmap.
• Streamline Team Operations: Support the team by identifying opportunities to make our processes more efficient, whether through better documentation, improved feedback loops, or simple automations.

Nice To Have:

• Familiarity with Automation Tools: Any experience playing with tools like Zapier or other no-code/low-code platforms is a bonus.
• Data Analysis Exposure: Basic experience with SQL, Python (Pandas), or data visualization tools like Tableau or Looker.
• Internship or Project Experience: Previous internships or relevant project work in a tech, startup, or marketplace environment.
• Customer-Facing Experience: Experience in a role where you directly interacted with users or customers (e.g., customer support, community management).

For CA based applicants:

• The base salary for this position is $80,000 - $100,000
• This position is eligible for equity in the form of stock options
• This position is eligible for Instawork benefits, including:
• A variety of medical, dental, and vision plans with coverage beginning on the date of hire
• Flexible paid time off
• At least 8 paid company holidays annually
• Phone stipend
• Commuter stipend
• Supplemental pay on qualified leaves
• Employee health savings accounts (HSA) contribution
• Flexible spending plans
• 401K plan
• Perkspot - discount program through Lumity

A variety of factors are considered when determining someone’s compensation including a candidate’s professional background, experience, and location. Final offer amounts may vary from the amounts listed above.

CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

Role Overview:

As a Modeling & Simulation Engineer: Operations Analysis at CHAOS, you will design, develop, execute, analyze, and validate models and simulations to deliver operational analysis and system performance assessment across defense, national security, and commercial programs. You will have freedom to move rapidly and use your expertise to apply rigorous statistical methods to analyze simulation outcomes, quantify system effectiveness, and communicate actionable insights to technical teams, leadership, and customers. Your work will directly inform critical decisions around sensor performance, mission planning, weapon effectiveness, and platform capability evaluation.

This is an exciting opportunity to be among the first members of a rapidly growing team of professionals dedicated to delivering highly impactful technologies to the defense, national security, and critical industry sectors.

Responsibilities:

• Scope, plan, and execute modeling and simulation efforts and studies aligned to program objectives, managing your competing priorities and timelines effectively.
• Develop, configure, and execute analysis using mission-level models and simulations such as AFSIM, ESAMS, Brawler, Ansys STK, and/or physics-based models to evaluate system and platform performance in operationally relevant scenarios.
• Apply statistical analysis techniques to simulation output data to quantify key performance metrics, identify trends, and characterize system effectiveness.
• Build, refine, and analyze models of sensors, communications systems, aircraft (including unmanned), weapons, and spacecraft within high-fidelity, engagement-level, and mission-level simulation frameworks.
• Develop and maintain Python-based analysis tools and pipelines for data processing, statistical analysis, and visualization.
• Document methodology, assumptions, and findings in technical reports and briefing materials, including data visualizations, and present results to both technical and non-technical audiences.
• Collaborate with engineering, business development, and customer teams to translate operational questions into well-structured analytical approaches.
• Maintain software development best practices including version control and reproducible analysis workflows.
• Support programs spanning DoD services, DARPA, intelligence community, and commercial customers.

Minimum Requirements:

• Bachelor's degree or higher in Computer Science, Aerospace/Software/Computer Engineering, Data Science, Statistics, Mathematics, Operations Research, Physics, or a related field.
• 5+ years of experience supporting defense, intelligence, or advanced technology programs through industry or government employment.
• Significant experience developing analytical tools and applying rigorous statistical methods to interpret and present results.
• Strong proficiency in Python and MATLAB, including standard scientific computing and visualization libraries (such as Pandas, Polars, NumPy, SciPy, Scikit-Learn, Matplotlib, Seaborn, CuPy, or PyTorch).
• Exceptional data visualization skills and comfort with developing CONOPS/OV-1 visuals and briefing packages.
• Proficiency with software development practices including version control and leveraging/validating outputs of AI-assisted coding tools.
• Prior experience in developing/working with rigid body/6 Degrees of Freedom physics simulations.
• Demonstrated ability to work independently and deliver analytical products with minimal oversight.
• Comfortable working on Linux-based systems and writing scripts and software for scalability.
• Eligibility to obtain a Top Secret / Sensitive Compartmented Information (TS/SCI) clearance.

Preferred Requirements:

• Demonstrated experience performing operations analysis studies using combat simulations (such as AFSIM, ESAMS, Brawler, and/or physics-based models), including interpreting results with statistical rigor and briefing key stakeholders.
• Extensive experience in radar sensor performance analysis, including quantification of key metrics and performance parameters, and conducting mission-level analysis of air-to-air, air-to-surface, surface-to-air, and electronic warfare engagements.
• Expertise in developing and validating models of sensors (especially radar), communications, aircraft (including unmanned aerial systems), weapons (especially missiles), or spacecraft in mission-level simulation environments such as AFSIM or Ansys STK.
• Exposure to Distributed Interactive Simulation (DIS) networking and visualization tools such as MAK VR-Forces, SIMDIS, or similar.
• Exposure to PX4 Guidance, Navigation & Control, and software-in-the-loop simulation with platforms such as X-Plane, Gazebo, or NVIDIA Omniverse.
• Experience supporting U.S. Department of Defense branches and related research labs such as DARPA, ONR, AFRL, or others, and commercial advanced technology programs.
• Active TS/SCI clearance.

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

CHAOS Industries is redefining modern defense with a multi-product portfolio that gives the ultimate advantage—domain dominance. The company's products are powered by Coherent Distributed Networks (CDN™), empowering warfighters, commercial air operators, and border protection teams to act faster, adapt rapidly, and stay ahead of evolving threats. 

CHAOS Industries was founded in 2022 and has raised a total of $1 billion in funding from leading investors, including 8VC, Accel, and Valor Equity Partners. The company is headquartered in Los Angeles, with offices in Washington, D.C., San Francisco, San Diego, Seattle, and London. For more information, please visit www.chaosinc.com.

Role Overview:

• Develop and deploy automated test infrastructure supporting RF and radar-related electronic systems.
• Own automation architecture for hardware control, test sequencing, and data acquisition.
• Improve reliability, repeatability, and scalability of lab and production test environments.
• Integrate software, hardware, and networking systems to enable efficient engineering validation and program execution.
• Support both development validation and production-level test automation needs

Responsibilities: 

• Develop and execute automated test solutions for RF and radar-related electronic systems
• Design and maintain Python-based automation for hardware control, test sequencing, and data collection
• Automate workstation provisioning and configuration using Ubuntu/Linux and Ansible
• Troubleshoot and resolve issues in automation scripts, lab systems, and networked test environments
• Configure and debug networking (static IPs, VLANs, interface diagnostics)
• Analyze and visualize test data to support engineering validation and program deliverables
• Collaborate with cross-functional engineering teams to improve reliability, repeatability, and efficiency of test systems
• Document test procedures, automation workflows, and troubleshooting processes

Minimum Requirements:

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Computer Science, or related field (or equivalent experience)
• 3–6 years of experience in test automation, hardware validation, or related engineering roles
• Proficiency in Python for test automation, including virtual environments and automated hardware test development
• Working knowledge of Ubuntu/Linux (command line, log analysis, NIC identification, system configuration)
• Experience with Ansible or similar tools for OS installation and workstation setup automation
• Networking fundamentals including static IP configuration, VLANs, and basic network troubleshooting
• Ability to independently debug and resolve integration issues between hardware, software, and network systems

Preferred Requirements:

• Experience with RF systems, radar systems, or high-frequency electronics
• Familiarity with RF test equipment (spectrum analyzers, signal generators, network analyzers)
• Experience supporting defense or aerospace programs
• Experience with data analysis and visualization tools (NumPy, pandas, Matplotlib, Plotly, tkinter)

Why CHAOS?

• Health Benefits: Medical, dental, and vision benefits 100% paid for by the company
• Additional benefits: 401k (+ 50% company match up to 6% of pay), FSA, HSA, life insurance, and more
• Our Perks: Free daily lunch, ‘No meeting Fridays’, unlimited PTO, casual dress code
• Compensation Components: Competitive base salaries, generous pre-IPO stock option grants, relocation assistance, and (coming soon!) annual bonuses
• Team Growth: 250 employees and counting across 5 global offices

The stated compensation range reflects only the targeted base compensation range and excludes additional earnings such as bonus, equity, and benefits. If your compensation requirements fall outside of the range, we still encourage you to apply. The salary range for this role is an estimate based on a range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. 

Recruiting Agencies: CHAOS Industries does not accept unsolicited resumes or outreach. Unsolicited submissions will not be reviewed or compensated.

#LI-onsite

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.

That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.

We’re looking for a Data Science Analyst to join the Data Science team. In this role, you will work in a fast-paced environment with diverse data sets and technologies to build production quality, scalable and automated solutions for a varied set of challenging data problems. Under the guidance of our Senior Data Scientists and Senior Data Science Analysts, you will have the freedom to utilize the latest technologies to solve challenging problems, create innovative applications from the ground up, and understand exactly what it takes to create a reliable online experience for our customers. This role collaborates closely with our technology teams to provide profound insights from your analysis, and optimize our business, with the ultimate goal of helping Tatari redefine the TV ad buying experience.

Responsibilities: 

• Automate data-driven tasks; design processes that require zero intervention
• Work cross-functionally within the organization to deliver integrated business solutions
• Provide ad-hoc data analysis, utilizing Python, PySpark, and SQL to identify and forecast trends and conduct deep-dive quantitative analyses to optimize client marketing performance
• Use best-in-class tools like Databricks, and Tableau to empower insightful analysis for advertising partners 

Qualifications:

• Bachelors degree in Business, Management, Economics, Accounting, Finance, or Computer and Information Science required
• 1-2 years of academic and/or professional experience in Data Manipulation Software (e.g., SQL, Python, Pandas)
• Demonstrated abilities to manipulate, analyze, and interpret large amounts of data and to organize findings and translate them into actionable insights using original or innovative techniques
• Extremely organized with great attention to detail
• Excellent ability to analyze information and think systematically
• Works well independently and as part of a team
• Ability to handle databases and understand technology-driven business tools
• A sense of curiosity and desire to learn! 

Benefits:

• Total compensation ($70,000 - $85,000)
• Equity compensation
• Health insurance coverage for you and your dependents
• 401K, FSA, and commuter benefits
• $150 monthly spending account
• $1,000 annual continued education benefit
• $500 Newbie Productivity Perk
• Unlimited PTO and sick days
• Monthly Company Wellness Day Off
• Snacks, drinks, and catered lunches at the office
• Team building events 
• Hybrid RTO of 2 days per week. THIS IS AN IN-OFFICE POSITION

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.

#LI-DNI

Tatari is on a mission to revolutionize TV advertising. Founded in 2016 to help transform the antiquated world of TV advertising through the intelligent application of AI and machine learning, Tatari helps some of the world’s fastest growing brands including Chime, Calm, Tecovas, Manscaped, Saatva, and Liquid I.V., reach their customers using linear and streaming TV ads. Our platform combines sophisticated media buying with proprietary analytics to turn TV advertising into an automated, digital-like experience, enabling businesses of any size to advertise on TV.

That approach has earned Tatari broad industry recognition, including being named Best CTV AdTech Platform in the 8th annual MarTech Breakthrough Awards, as well as honors from Digiday (Best Connected TV Platform), AdExchanger (Most Innovative TV Advertising Technology), and Business Insider (Hottest AdTech Companies). Tatari has also been recognized as the Best Place to Work by Inc. Magazine. Backed by an executive team of former founders and senior leaders from companies including Shazam, TrueCar, AdapTV, LiveRail, Amazon, Google, Meta, Microsoft, and Yahoo, Tatari continues to scale rapidly as TV advertising enters its next major era.

We’re looking for a Data Science Analyst to join the Data Science team. In this role, you will work in a fast-paced environment with diverse data sets and technologies to build production quality, scalable and automated solutions for a varied set of challenging data problems. Under the guidance of our Senior Data Scientists and Senior Data Science Analysts, you will have the freedom to utilize the latest technologies to solve challenging problems, create innovative applications from the ground up, and understand exactly what it takes to create a reliable online experience for our customers. This role collaborates closely with our technology teams to provide profound insights from your analysis, and optimize our business, with the ultimate goal of helping Tatari redefine the TV ad buying experience.

Responsibilities: 

• Automate data-driven tasks; design processes that require zero intervention
• Work cross-functionally within the organization to deliver integrated business solutions
• Provide ad-hoc data analysis, utilizing Python, PySpark, and SQL to identify and forecast trends and conduct deep-dive quantitative analyses to optimize client marketing performance
• Use best-in-class tools like Databricks, and Tableau to empower insightful analysis for advertising partners 

Qualifications:

• Bachelors degree in Business, Management, Economics, Accounting, Finance, or Computer and Information Science required
• 1-2 years of academic and/or professional experience in Data Manipulation Software (e.g., SQL, Python, Pandas)
• Demonstrated abilities to manipulate, analyze, and interpret large amounts of data and to organize findings and translate them into actionable insights using original or innovative techniques
• Extremely organized with great attention to detail
• Excellent ability to analyze information and think systematically
• Works well independently and as part of a team
• Ability to handle databases and understand technology-driven business tools
• A sense of curiosity and desire to learn! 

Benefits:

• Total compensation ($70,000 - $85,000)
• Equity compensation
• Health insurance coverage for you and your dependents
• 401K, FSA, and commuter benefits
• $150 monthly spending account
• $1,000 annual continued education benefit
• $500 Newbie Productivity Perk
• Unlimited PTO and sick days
• Monthly Company Wellness Day Off
• Snacks, drinks, and catered lunches at the office
• Team building events 
• Hybrid RTO of 2 days per week. THIS IS AN IN-OFFICE POSITION

At Tatari, we believe in the importance of cultivating teams with diverse backgrounds and offering equal opportunities to all. We strive to create a welcoming, inclusive environment where every team member feels valued and diversity is celebrated.

#LI-DNI

The Role

We’re seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints.

You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions.

You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions.
• Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale.
• Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process.
• Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift.
• Tell the story: Communicate trade-offs and impact to execs and non-technical partners; make the complex understandable and actionable.

What You've Done

• 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred.
• Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost).
• Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement.
• Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL.
• Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact.
• Excellent communication skills, with the ability to clearly articulate modeling assumptions, tradeoffs, and impact to both technical and non-technical audiences.

Nice to have:

• Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety.
• Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring.
• Experience selecting and applying appropriate causal inference approaches to evaluate model and policy impact, including methods such as uplift modeling, synthetic control, and BSTS.

What We Offer

• Accelerated Growth Environment: An environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
• Top Tier Compensation Package: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to recharge as needed.
• Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.

As a Solution Architect you are responsible for discovering customer requirements, validation of customer data, and providing product expertise in the form of software demonstrations and asking probing questions to understand customer expectations and the appropriate scope for implementation. You will be a deep technical expert on how Avathon's software delivers technical value and how it is configured and deployed into customer environments. You will use your technical expertise and hands-on analytic capabilities to understand, communicate, and validate the customer’s data and environment against the solution requirements.
Join us in:

• Partnering with Product and Services teams to stay up-to-date on capabilities, roadmap, and technical delivery
• Clearly messaging the technical value and limitations of our products in presentations and conversations
• Developing and delivering technical content to share across the broader team to help Marketing and Sales message the solution capabilities to both technical and non-technical audiences
• Gaining customer trust by asking pointed questions and being an excellent listener during calls and meetings
• Exceeding customer expectations with regards to responsiveness, professionalism, and honesty
• Validating and mapping customer technical requirements to Avathon product capabilities while taking into account the available data, IT infrastructure, and security requirements.
• Consolidating and communicating customer feedback to product and marketing teams
• Providing web and in-person product and data presentations and demonstrations of Avathon's software to potential customers and partners
• Building and delivering demos using customer data to tell meaningful stories while documenting your work for both internal and external collateral
• Keeping excellent documentation of all customer interactions
• Scoping and writing customer proposals and responding to RFPs
• Scoping and delivering Proof of Concept engagements using customer provided data

You'll Have:

• At least 8 years experience as a PreSales engineer, software engineer, technical sales, technical consulting, or similar work experience
• At least 5 years demonstrated experience with Python and familiar with Jupyter Notebooks, Pandas, and other libraries to visualize and model data using cloud-based VMs (Google, Azure, AWS)
• At least 6 years experience in customer facing roles
• A certificate or demonstrated experience in Data Science or Machine Learning
• Excellent written and verbal communication skills
• Excellent listening and documentation skills
• Demonstrated leadership in coordinating and driving cross-functional efforts
• Flexibility to travel 20% or as business needs require

It would be great if you had:

• Experience working in industrial environments with direct exposure to industrial safety, operations, and equipment maintenance programs
• Experience with computer vision or vision-based AI modeling
• Experience or a desire to participate in public speaking and promoting thought leadership in the domain of applied AI
• Experience configuring and deploying cloud services for compute and data storage

What are the benefits and perks at Avathon?
Below are some highlights we offer to our U.S. full-time employees - we’d love to connect and share more!

• Evolving culture with the opportunity to drive new ideas and technology
• Stock Option Grants
• Medical Coverage, and Parental Leave Plans
• 401k with Employer Match
• Monthly Technology Allowance
• Newly renovated office space located near Pleasanton, CA - including fully stocked beverage and snack areas!
• Contract and temporary roles are not eligible for the above benefits.

Pay Range: $225k OTE salary. Pay for this position is based on a number of factors including geographic location and may vary depending on job-related knowledge, skills, and experience. This role is not remote. Candidates must be based in the Bay area, CA and are expected to report to our office 5 days a week.

C3 AI is looking for Senior Software Engineers to join the rapidly growing Data org within the Platform Engineering department. Successful candidates will get the opportunity to work on high-value technologies at the intersection of large-scale distributed systems, data infrastructure, and machine learning. You will design, develop, and maintain various features in a highly scalable and extensible AI/ML platform for large-scale applications, involving data science, distributed systems, and multi-cloud strategy.

You will be given opportunities to take ownership of components, collaborate to drive technical direction, and work on interesting, impactful projects. Join us in building the next-generation AI/ML platform at petabyte level scale that powers some of the world’s largest companies in Energy, Financial Services, Utilities, Health Care, Aerospace, Defense, etc. Accelerate your career in the leading enterprise AI company that is in a hyper-growth trajectory.

Responsibilities:

• Design and develop infrastructure and services to enable data pipelines for petabyte level scale and more.
• Design and develop abstractions over datastores such as Cassandra, PostgreSQL, Snowflake, etc.
• Design and develop file system abstractions over AWS S3, Azure Blobs, HDFS, etc.
• Design and develop connectors to various external data stores.
• Design and develop distributed system components for stream processing, queueing, batch processing, analytics engines, etc.
• Develop and maintain industry-leading, high-performance APIs for AL/ML applications.
• Develop and maintain features for distributed computations over large-scale data for ML workflows.
• Design and develop ML-specific data-systems such as feature stores and behavioral frameworks such as recommendation engines.
• Design and develop integrations with distributed computing technologies such as Apache Spark, Ray, etc. for data exploration and ML workload orchestration.
• Design and develop integrations with data analysis libraries such as Pandas, Koalas, etc.
• Develop and production AI/ML models for failure prediction, data schema inferencing, etc.
• Work on frameworks for performance, scalability, and reliability tracking over different components of a highly extensible AI/ML platform.
• Work with architects, product managers, and software engineers across teams in a highly collaborative environment.
• Participate and provide insights in technical discussions.
• Write clean code following a test-driven methodology.
• Deliver commitments promptly following agile software development methodology.

Qualifications:

• Bachelor of Science in Computer Science, Computer Engineering, or related fields.
• A minimum of 5 years of work experience in a fast-paced software company.
• Strong understanding of Computer Science fundamentals.
• High proficiency in coding with Java, C++, C#, or some other compiled language. Python would also be acceptable.
• Strong competency in object-oriented programming, data structures, algorithms, and software design patterns.
• Experience with version control systems such as Git.
• Experience with large-scale distributed systems.
• Experience with any public cloud platform (AWS, Azure, GCP).
• Some familiarity with distributed computing technologies (e.g., Hadoop, Spark, Kafka). Familiarity with managed versions of these technologies on public cloud platforms is also acceptable.
• Familiarity with technologies in the modern data science/analysis and engineering ecosystem (e.g., Pandas, Koalas).
• Good verbal and written technical communication ability to facilitate collaboration.
• Thrive in a fast-paced, dynamic environment and value end-to-end ownership of components.
• Intellectually curious and open to challenges.

Preferred Qualifications:

• Advanced degree in engineering, sciences, or related field.
• Experience with Agile development methodology.
• Experience developing and working with REST and/or GraphQL APIs.
• Experience building scalable and reliable data pipelines.
• Experience with integration of data from multiple sources.
• Experience working with analytics and/or data processing engines.
• Experience developing distributed computation over large-scale data.
• Experience working with distributed computing frameworks (e.g., Hadoop, Spark, Kafka).
• Experience with data science/analysis libraries (e.g., Pandas, Koalas).
• Experience with task schedulers in distributed computing (e.g., Spark, Ray, Dask).
• Familiarity with machine learning workload orchestration in a distributed computing environment.
• Familiarity with workflow execution and/or optimization using DAGs, ideally for machine learning use-cases.
• Conceptual understanding of orchestration and resource provisioning systems (Kubernetes)