About the team

Roku pioneered in developing operating system for TVs. Tv Technology team within Roku TV NPI group is focused on building TVs with best Audio Quality , Picture Quality and Enable innovation technology. 
With tens of million TVs sold across many countries, thousands of streaming channels and billions of hours watched over the Roku TVs, having best Audio Quality & Picture Quality is crucial.

About the role

We are looking for a creative and passionate Machine Learning (ML) / Deep Learning (DL) Engineer to join the Roku TV team. You will explore Picture Quality (PQ) and Audio Quality (AQ) improvements using AI in a resource-constrained environment, pushing the limits of what is possible in TV technology. Additionally, this role will involve applying state-of-the-art ML techniques to different PQ and AQ related tasks. You will play a critical role in building scalable systems and algorithms that enhance streaming experiences for millions of users worldwide.

For California Only - The estimated annual salary for this position is between $135,000 - $185,000 annually. Compensation packages are based on factors unique to each candidate, including but not limited to skill set, certifications, and specific geographical location. This role is eligible for health insurance, equity awards, life insurance, disability benefits, parental leave, wellness benefits, and paid time off.

What you’ll be doing

• Explore and implement AI-driven Picture Quality and Audio Quality improvements for Roku TV
• Apply advanced ML techniques in the optimization of models to enhance video and audio processing pipelines
• Research, understand, and implement technical papers on ML/DL to solve complex challenges
• Collaborate with engineering teams and cross-functional partners to translate business requirements into technical solutions
• Run experiments and analyze results against critical business KPIs

We’re Excited If You Have

• 1+ years of experience applying Machine Learning to concrete problems at scale
• Strong CS fundamentals; ability to write efficient algorithms with ease
• Hands-on experience with Machine Learning / Deep Learning frameworks like TensorFlow or PyTorch
• Proficiency in coding firmware development using C++
• Proficiency in coding ML/DL algorithms using Python
• Solid understanding of DL fundamentals, including RNN, CNN, and multi-modal models
• Familiarity with video processing pipelines and audio pipelines
• AI literacy and curiosity—whether through previous work or personal exploration
• Excellent communication skills, strong work ethic, and works with minimum supervision 
• Have hands-on experience with edge devices like jetson nano, kadas, and similar
• Research background preferred; ability to understand and implement technical papers on ML/DL
• Published papers in the field of ML/DL are a bonus
• Hold an MS or PhD in Computer Science, Electrical Engineering, or related fields - Preferred

#LI-DH2

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.

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.

 Who We Are

2K is headquartered in Novato, California and is a wholly owned label of Take-Two Interactive Software, Inc. (NASDAQ: TTWO). Founded in 2005, 2K Games is a global video game company, publishing titles developed by some of the most influential game development studios in the world. Our studios responsible for developing 2K’s portfolio of world-class games across multiple platforms, include Visual Concepts, Firaxis, Hangar 13, CatDaddy, Cloud Chamber, 31st Union, HB Studios, and 2K SportsLab. Our portfolio of titles is expanding due to our global strategic plan, building and acquiring exciting studios whose content continues to inspire all of us! 2K publishes titles in today’s most popular gaming genres, including sports, shooters, action, role-playing, strategy, casual, and family entertainment.

Our team of engineers, marketers, artists, writers, data scientists, producers, thinkers and doers, are the professional publishing stewards of 2K’s portfolio currently includes several AAA, sports and entertainment brands, including global powerhouse NBA®️ 2K,  renowned BioShock®️, Borderlands®️, Mafia, Sid Meier’s Civilization®️ and XCOM®️ brands; popular WWE®️ 2K and WWE®️ SuperCard franchises, TopSpin 2K25, as well as the critically and commercially acclaimed PGA TOUR®️ 2K.

At 2K, we pride ourselves on creating an inclusive work environment, which means encouraging our teams to Come as You Are and do your best work! We encourage ALL applicants to explore our global positions, even if they don’t meet every requirement for the role.  If you're interested in the job and think you have what it takes to work at 2K, we encourage you to apply!

 What You Will Do

 2K Games is building a world-class data ecosystem to power real-time analytics, machine learning, and game intelligence across all our franchises. We are looking for a Senior Product Manager, Data Science to drive the vision, strategy, and execution of our data science strategies and products, partnering with game studios and analytics teams to enable enhanced player experiences.

This role requires a blend of strategic development, product management expertise, and technical understanding of data science and machine learning (ML) methodologies. The ideal candidate will seamlessly integrate data-driven strategies with player-centric goals, ensuring AI and analytics improve game design, live operations, and business intelligence.

Strategic Vision & Product Leadership

• Develop and implement the product strategy for 2K’s central data science platform, partnering with Data Scientists across our gaming business units to drive predictive analytics, player personalization, and real-time decision-making;
• Collaborate with the Director of Product, 2K Data to align the data engineering roadmap with customer objectives and player-centric outcomes;
• Define and prioritize a high-impact data science roadmap to lead a team of central data scientists in driving a variety of use cases such as player retention modeling, dynamic content generation, and real-time fraud detection. 

Data Science Platform Development

• Lead the development of reusable and extensible machine learning models, feature engineering pipelines, and ML-driven insights using tools like Databricks, MLflow, and SageMaker;
• Ensure data science initiatives integrate seamlessly with the real-time data infrastructure, supporting streaming analytics, AI-powered LiveOps, and dynamic matchmaking systems;
• Establish and maintain self-service tools that enable game teams to experiment with and deploy AI models independently;
• Support the build and enhancement of the central ML feature store;
• Monitor and optimize model performance in production environments, using MLOps standard methodologies;
• Implement governance frameworks to ensure AI models adhere responsibly to data privacy, security, and compliance standards (e.g., CCPA, GDPR). 

Cross-Functional Collaboration

• Work closely with data scientists across game studios and business units to understand their data science needs and to provide data-driven solutions at the pace they need them;
• Act as a strategic liaison between data scientists and product teams, ensuring model outputs are actionable, reliable, and aligned with business goals;
• Promote a culture of experimentation and rapid iteration, supporting game studios with A/B testing frameworks, predictive analytics, and personalization engines.
• Find opportunities to enhance game design and player engagement through advanced analytics and machine learning.

 What You Need

• 7+ years of experience in product management with a focus on data science, analytics, or ML-driven products
• 5+ years of experience in gaming, technology, or entertainment industries;
• Strong understanding of data science methodologies, such as predictive modeling, natural language processing, and computer vision;
• Experience with data science tools and platforms, such as Python, SQL, Databricks,TensorFlow, and R;
• Customer-focused mentality with focus on the Why and What without getting lost in the What and the How;
• Consistent track record of delivering data science products and features from ideation to production, with measurable business impact;
• Ability to translate complex data insights into clear product strategies and business opportunities;
• Knowledge of real-time analytics platforms, streaming data processing, and feature store management;
• Familiarity with data governance frameworks, model risk management, and MLOps standard processes preferred;
• Advanced degree or equivalent experience in Data Science, Machine Learning, Computer Science, or a related field preferred.

The pay range for this position in California at the start of employment is expected to be between $109,800 and $162,480 per Year. However, base pay offered is based on market location, and may vary further depending on individualized factors for job candidates, such as job-related knowledge, skills, experience, and other objective business considerations. Subject to those same considerations, the total compensation package for this position may also include other elements, including a bonus and/or equity awards and eligibility to participate in our 401(K) plan and Employee Stock Purchase Program. Regular, full-time employees are also eligible for a range of benefits at the Company, including: medical, dental, vision, and basic life insurance coverage; 14 paid holidays per calendar year; paid vacation time per calendar year (ranging from 15 to 25 days) or eligibility to participate in the Company’s discretionary time off program; up to 10 paid sick days per calendar year; paid parental and compassionate leave; wellbeing programs for mental health and other wellness support; family planning support through Maven; commuter benefits; and reimbursements for fitness-related expenses.

As an equal opportunity employer, we are committed to ensuring that qualified individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform their essential job functions, and to receive other benefits and privileges of employment. Please contact us if you need reasonable accommodation.

Please note that 2K Games and its studios never uses instant messaging apps or personal email accounts to contact prospective employees or conduct interviews and when emailing, only use 2K.com accounts. 

#LI-Onsite

About the Team

The Counter Intrusion MSE team develops systems that provide force protection capabilities, monitoring the perimeter of secure areas, land or sea, for approaching people, vehicles, and vessels. We live in a world where security officers are increasingly overwhelmed by sensor data feeds. Our products leverage advanced sensor fusion and autonomy to seamlessly render activity in the environment to Lattice's common operating picture. This relieves operators of our system from a ton of burden and allows our customers to get more done with fewer personnel. Increasingly, Counter Intrusion MLEs are working on projects to bring customers' existing legacy security systems into the Lattice ecosystem. Key to this effort is building scalable software solutions so that we can service many customers without requiring bespoke software for each one. The Counter Intrusion team is responsible for the development, testing, deployment, and sustainment of our family of systems. We work closely with other teams from product, engineering, sales, logistics, operations, and mission success.

About the Role

We are looking for a Machine Learning Engineer to apply the latest research to solve our toughest problems. This role will be responsible for owning the whole machine learning stack for the Counter Intrusion team. You will design and train multi-sensor object detection models for perception on edge compute devices that push the boundaries of what's possible with our sensors. You will develop learning algorithms to optimize the behavior of autonomous systems. You will also be responsible for the end-to-end design, implementation, and performance of the ML stack, including the infrastructure for data collection and training. Your work will directly impact Anduril's ability to deliver cutting-edge defense technology, with the opportunity to identify and develop novel ML applications across our product portfolio.

Responsibilities

• Propose and prototype innovative solutions to solve real-world problems, leveraging the latest state-of-the-art techniques in the field
• Develop and maintain core ML pipelines
• Train and deploy deep learning models for real-time applications
• Collaborate cross-functionally with camera, systems and labeling teams
• Curate datasets for evaluating performance and comparing performance trends over time
• Provide technical mentorship to other junior ML engineers

Required Qualifications

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field
• 6+ years of experience developing, benchmarking and optimizing ML algorithms on large-scale datasets
• Strong Deep Learning and CV background
• Proficiency in C++ development in a Linux environment
• Experience with Python development and deep learning frameworks such as PyTorch, JAX and TensorFlow
• Experience deploying models with TensorRT and ONNX
• Optimize on-device inference and vision kernels across CPU/GPU/NPU
• Track record of developing and deploying CV models from R&D to production
• Experience writing and maintaining automated continuous integration tests
• Knowledge of system profiling and tuning for latency, memory and power efficiency
• Ability to conduct experiments, ablation studies and create highly detailed reports
• Eligible to obtain and maintain a U.S. Secret security clearance

Preferred Qualifications

• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic Change Detection, Depth Estimation, Model Pruning and Compression
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Camera Models, RGB-D and LIDAR Sensor Fusion, Optical Flow
• Experience troubleshooting and analyzing remotely deployed software systems
• 1 year of experience in a technical leadership role

Snapshot 

At Google DeepMind, our research team is dedicated to tackling the most complex challenges in online information quality. We strive to advance the state of the art by developing innovative solutions to detect manipulated media and misleading narratives, ensuring the integrity of digital discourse. A prominent example of our scientific discovery is Backstory. Our interdisciplinary work spans provenance analysis and the creation of tools for AI-assisted information literacy, leveraging our technologies for the widespread public benefit of a safer online environment. We thrive in a supportive environment that encourages rapid prototyping and iteration, driving our research achievements directly into Google’s flagship models, including Gemini.

About us 

Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.

We’re a dedicated scientific community, committed to “solving intelligence” and ensuring our technology is used for widespread public benefit. 

We’ve built a supportive and inclusive environment where collaboration is encouraged and learning is shared freely. We don’t set limits based on what others think is possible or impossible. We drive ourselves and inspire each other to push boundaries and achieve ambitious goals.

The role

To succeed in this role, you will need to be passionate about advancing information literacy using machine learning and other computational techniques. You'll join an interdisciplinary team of domain experts, ML researchers, and engineers to research and build multimodal reasoning systems and Vision-Language Models (VLMs) to assess the trustworthiness of media (images, audio, and videos) on the internet.   

Key responsibilities:

• Plan and perform rapid prototyping of computer vision and multimodal machine learning techniques applied to determining authenticity of media information.
• Design and train multimodal models capable of complex visual reasoning.
• Undertake exploratory analysis to inform experimentation and research directions.
• Engage with product teams to drive the development of our research.
• Implement tools, libraries, and frameworks to speed up and enable new research.
• Report and present research findings, software developments, experimental results, and data analysis clearly and efficiently.
• Collaborate with internal and external scientific domain experts.

About you

In order to set you up for success as a Research Engineer at Google DeepMind, we look for the following skills and experience:

• PhD/Master’s degree in Computer Science, AI, ML, or equivalent practical experience.
• At least 2 years of relevant experience developing computer vision techniques or multimodal machine learning models.
• Experience in software development using Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a proven track record of building high-quality research prototypes and systems.
• Quantitative skills in math and statistics.
• Experience exploring, analysing and visualising data.

In addition, the following would be an advantage: 

• Experience in training and deployment of large-scale models.
• Experience with Video Understanding
• Experience with Large Language Models, prompt engineering, few-shot learning, post-training techniques, and evaluations.
• A proven track record of research or engineering achievements, such as publications in peer-reviewed conferences or journals.

When assessing technical background we will take a holistic view of the mix of scientific, ML and computational experience. We do not expect you to be an expert in all fields simultaneously.

At Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.

The US base salary range for this full-time position is between 174,000 USD - 252,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

About the Role
We are looking for an AI Scientist to join our team at the intersection of machine learning and single-cell biology. This role will focus on developing and applying foundation models to large-scale perturb-seq and single-cell datasets to uncover new biological mechanisms and therapeutic opportunities. You will help design scalable ML architectures that can extract insight from high-dimensional perturbation data and integrate across multi-omic modalities.

Key Responsibilities

• Design, train, and refine foundation models tailored to perturb-seq and other single-cell datasets.
  Build pipelines for preprocessing, normalization, and integration of large-scale single-cell and perturbation data.
• Apply ML/AI approaches to model cellular responses to perturbations and identify causal biological insights.
• Collaborate with experimental biologists to align computational methods with experimental design and discovery goals.
• Develop multimodal integration approaches across transcriptomic, epigenomic, and proteomic single-cell readouts.
• Publish methods and results in top scientific journals and present at conferences.
  
  

Qualifications

• PhD or equivalent in Computational Biology, Computer Science, Bioinformatics, or related discipline.
• Strong expertise in single-cell data analysis, particularly perturb-seq 
• Hands-on experience with foundation models or large-scale self-supervised learning (e.g., transformers, variational autoencoders).
• Strong coding skills in Python, ML frameworks (PyTorch/TensorFlow), and single-cell analysis tools (Scanpy, Seurat).
• Experience in developing scalable ML methods for large biological datasets.
  
  

Preferred

• Background in causal inference, generative models, or representation learning for biological systems.
• Familiarity with multi-omics integration and cross-modal foundation models.
• Track record of impactful publications in computational biology, machine learning, or related fields.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $150,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
We are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.

This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.

Key Responsibilities

• Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
• Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
• Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
• Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
• Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
• Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
• Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.

Qualifications

• Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
• Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
• Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
• Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
• Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).

Preferred

• Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
• Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
• Understanding of privacy, security, and regulatory considerations in healthcare AI.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

The Impact You’ll Be Contributing to Moloco:

As a Senior Machine Learning Engineer on Moloco’s Ads Quality team, you’ll design and scale machine learning systems that directly improve ad relevance, ranking, and optimization. Your work will have a measurable impact on advertiser performance, revenue efficiency, and the overall user experience across Moloco’s ad platform.

The Opportunity:

• Design, build, and deploy large-scale ML systems for ad ranking, click-through prediction, and conversion optimization
• Develop and operate production pipelines that process hundreds of millions of ad requests per day with low-latency requirements
• Collaborate directly with customers and partners in Mandarin to understand business goals and deliver data-driven ML solutions
• Apply systematic, reproducible approaches to model training, evaluation, and continuous improvement
• Partner with the Machine Learning Infrastructure and Data teams to improve tooling, deployment pipelines, and training efficiency
• Lead design and code reviews to promote technical excellence and standardize ML practices across Ads teams
• Diagnose model performance, identify optimization opportunities, and execute experiments that drive measurable results
• Mentor engineers on best practices for ML experimentation, productionization, and scaling
• Work cross-functionally with product, infrastructure, and business teams to align technical innovations with product goals

How Do I Know if the Role is Right For Me?

• You have 7+ years of experience building and deploying ML systems at scale, ideally in AdTech, recommender systems, or search/ranking domains
• You’ve shipped models that directly improved key product or business metrics such as CTR, CVR, or ROI
• You’re fluent in Mandarin Chinese and skilled at collaborating with customers or partners in technical discussions
• You have strong software engineering fundamentals: data structures, algorithms, and system design and proficiency in Python (C++ or Java a plus)
• You’re experienced with modern ML frameworks such as PyTorch, TensorFlow, or JAX
• You’ve worked with distributed data and compute systems like Apache Beam, Dataflow, or Flume
• You understand how to build robust ML pipelines including data versioning, feature engineering, retraining, and model monitoring in production
• You have experience optimizing inference performance on GPUs, TPUs, or similar hardware accelerators
• You thrive in fast-moving, ambiguous environments and can translate complex technical work into measurable business outcomes
• You value collaboration, accountability, and building systems that scale across teams and markets

Expression of Interest

We know that for the most talented engineers, the right opportunity is about more than just a job title, it’s about the right challenge at the right time. Even if our current openings don't perfectly fit your timing and interests today, we still want to hear from you. We view this as a priority pathway to connect with curious, driven MLEs whose unique expertise can help us architect the next generation of planet-scale ML systems. 

At Moloco, our mission is to empower the global digital economy by turning massive first-party data into measurable business outcomes. Whether it’s optimizing real-time bidding for Moloco Ads or building AI-native stacks for Streaming and Commerce, we’re looking for engineers to help us lead the shift toward a more performance-driven, AI-powered internet.

If you’re excited to scale and innovate in a fast-moving environment, share your profile and we will reach out the moment we see a potential match for your experiences and future goals.

About the Role

As a Machine Learning Engineer at Moloco, you will design, train, and deploy the large‑scale models that power our programmatic advertising and commerce media products. You will work at the heart of our real-time bidding and pricing systems, helping shape an end-to-end ML ecosystem that processes billions of daily events. Your work will directly improve marketplace performance for global advertisers and publishers by optimizing for relevance, ROI, and user experience at a scale few companies can match.

The Opportunity

• Architect and iterate on high-performance models that improve ad relevance, click-through rates, and conversion performance.
• Productionize and maintain scalable ML pipelines - from data ingestion to online inference - on top of planet-scale infrastructure.
• Extract insights from massive datasets of user behavior and auction signals to define new features and refine modeling strategies.
• Translate business goals (revenue, ROI, engagement) into concrete modeling challenges and success metrics in collaboration with Product and Data Science.
• Validate innovation through rigorous experimentation, including A/B tests, offline evaluations, and counterfactual analyses.
• Balance marketplace health by implementing models that harmonize advertiser value with a high-quality user experience.
• Enhance system reliability by refining feature stores, monitoring data quality, and establishing robust debugging practices.
• Drive platform evolution, contributing to ML tools and guidelines that increase experimentation velocity and deployment speed.
• Optimize for performance, partnering with Infra teams to reduce latency and improve throughput for low-cost, high-scale decisioning.
• Elevate technical excellence by sharing best practices in modeling and production ML with the broader engineering team.

Expertise We Value:

MLEs at Moloco are hands-on builders of some of the world’s highest-scale ML workloads. They bridge technical innovation with global revenue outcomes, owning the critical systems that define our next generation of machine learning and optimization platforms.

While every journey is unique, we find that the most successful MLEs at Moloco bring a deep technical foundation in the following areas:

• Production ML at Scale: 5-12+ years of experience delivering ML solutions in high-stakes production environments (e.g., Ads, Recommenders, Search, or Marketplaces), with a track record of scaling models for massive throughput and low-latency requirements.
• Algorithmic Mastery: A strong foundation in ML and statistics applied to real-world business challenges, with expertise in areas such as ranking, calibration, exploration-exploitation, causal inference, or multi‑objective optimization.
• Full-Lifecycle Engineering: Deep understanding of the end-to-end ML lifecycle, including data pipelining, feature engineering, model architecture, inference optimization, and the deployment of models into online systems.
• Technical Versatility: Proficiency across a modern ML toolkit (Python, SQL, and frameworks like TensorFlow or PyTorch) and experience leveraging data processing stacks like Spark, Beam, or Flink to deliver results at scale.
• Operational Stewardship: Experience ensuring the long-term health of ML systems in live environments—monitoring performance, diagnosing drift, and iterating based on real-world feedback to maintain measurable impact.
• Technical Mentorship: A passion for advancing the team’s collective bar by sharing best practices for large-scale ML systems and guiding the technical direction of complex machine learning initiatives.

Our Tech Stack:

• Languages: Python, Go, C++
• ML Frameworks: TensorFlow, PyTorch, JAX
• Infrastructure: GCP, AWS, Kubernetes, Spark, BigQuery, BigTable

How You Work: 

• Your ethos is ownership
• You thrive in ambiguity and enjoy partnering with others to shape vague requirements into clear roadmaps with pragmatic tradeoffs.
• You take shared accountability for the end-to-end journey; communicating progress, surfacing risks early, and following through to ensure your work creates measurable value.
• You demonstrate strong judgment under uncertainty. 
• You prioritize based on long-term impact, over short-term noise, making deliberate decisions when information is incomplete.
• You explicitly weigh tradeoffs like speed vs. quality and remain agile enough to adjust your approach thoughtfully as new information/data emerges.
• You lead through clarity and active listening. 
• You reduce ambiguity for the team by asking the right questions upfront, tailor your communication to your audience, document your decisions, and bring helpful structure to complex discussions. 
• You provide thoughtful, evidence-based feedback when needed and align behind decisions once they are made.
• You collaborate early, instead of solving in isolation.
• You build trust across the organization by listening first and navigate conflicting needs with empathy, creating buy-in around priorities and scope. 
• You navigate technical tensions productively, disagreeing thoughtfully while maintaining momentum and strengthening professional relationships.
• You fall in love with the problem, not the solution
• You build for the long run, looking beyond immediate tasks to understand root causes, second-order effects, and the long-term health of our ML ecosystem. 
• When something breaks, you don’t just patch it; you seek structural improvements that prevent recurrence and elevate the technical bar for the entire organization.
• You prioritize customer impact and take action to make it real.
• You prioritize effective solutions that drive business impact over technical elegance, spotting opportunities that others might overlook. 
• You have the initiative to turn ideas into outcomes and the agency to identify and fix gaps, even when they aren’t yet on the formal roadmap.

You can apply for this role through our Open Positions page (or through our Internal Job Board if you are a current employee). We will review submissions on an ongoing basis.

What You’ll Do:

As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $160,000.00 - $180,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

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.

What You’ll Do:

As a Staff AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $190,000 - $240,000 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

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.

What You’ll Do:

As a Principal AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $270,000.00 - $340,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

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.

What You’ll Do:

As a strong AI and ML fundamentalist who is an expert at developing cutting-edge AI solutions to complex problems, you will develop code that eventually integrates into production and be responsible for:

• Design, implement, and evaluate novel machine learning and deep learning algorithms.
• Iterate on AI model development; starting from the data needed for training, architecture, input/output representations, evaluation, and deployment. 
• Collaborate with other researcher engineers to prototype and validate complex solutions from academic literature.
• Conduct experiments to benchmark new techniques and evaluate model behavior.
• Develop tools and frameworks to support scalable and reproducible research and development.
• Communicate research findings to leadership in a concise, and convincing manner.
• Stay current with the latest developments in AI/ML and identify relevant innovations.
• Assist in transitioning research prototypes into production-ready systems.

What You Need:

• M.S or PhD degree in Computer Science, or Computer Engineering with strong emphasis on AI and ML.
• Enjoys solving less-defined and complex problems
• Familiarity with good SW practices and development, including code quality, version control, etc.
• Very strong with ML frameworks such as Pytorch, or Tensorflow
• Good understanding of Transformer architectures, attention mechanisms, multi-modal foundation models, diffusion policies, fine-tuning, model distillation, mixture of experts, and other similar topics.
• Has strong ability to debug and determine requirements for AI models in terms of data, training, and evaluation.
• Is up to date with research literature and recent ML techniques and methodologies.

Bonus Qualifications:

• Experience with Reinforcement Learning, self-supervised training, and imitation learning is a plus.
• Experience developing VLA (Vision Language Action) models for robotic manipulation and mobility is a plus.
• Experience developing production AI models is a plus.
• Publications at top conferences are a plus.

Please note that this job description is intended to provide a general overview of the position and does not include an exhaustive list of responsibilities and qualifications

At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company’s business strategy. For this position we are targeting a base pay between $160,000.00 - $180,000.00 Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.

Archer is proud to be an Equal Opportunity employer committed to diversity and inclusivity in the workplace. All aspects of employment are decided on the basis of merit, qualifications, and business needs. We do not discriminate based upon race, color, religion, sex, sexual orientation, age, national origin, disability status, protected veteran status, gender identity or any other characteristic protected by federal, state or local laws.

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.

WHAT YOU’LL DO

• Guide DSP engineers in the execution of DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 7+ years with a BSEE or related field 
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

WHAT YOU’LL DO

• Guide DSP engineers in the execution of DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 7+ years with a BSEE or related field 
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

ABOUT THE TEAM

Anduril’s Tactical Recon & Strike (TRS) is a division with two missions: 1) build highly capable autonomous drones, and 2) build solid rocket motors at scale. We transform products like Ghost, Anvil, Bolt, and Altius from early concepts into fully operational capabilities by partnering closely with specialist engineering, operations, and production teams. Through our Anduril Rocket Motor Systems (RMS) team, we design and manufacture solid rocket motors using advanced materials, proprietary formulations, and high-volume production methods—delivering safe, reliable propulsion systems that support a wide range of mission requirements. TRS hires software engineers & hardware engineers, who are excited to build across a diverse and powerful portfolio—from autonomous aerial systems to high-performance solid rocket motors. Our teams contribute to highly capable autonomous robotics systems and propulsion products that operate reliably in the most demanding mission environment.

ABOUT THE JOB

We are seeking Senior Software Engineers specializing in Computer Vision and Machine Learning Engineering. You will leverage cutting-edge research to solve our most challenging perception problems for our UAVs, bringing deep expertise in Object Detection, Object Tracking, or related perception domains. This role requires hands-on proficiency in C++ and/or Python within a Linux environment. If you are passionate about tackling complex technical challenges in computer vision and perception, we encourage you to apply.

This position will be located at our headquarters in Costa Mesa, CA (relocation benefits provided).

WHAT YOU’LL DO

• Propose and prototype innovative solutions to solve real world problems, leveraging the latest state-of-the-art techniques in the field.
• Develop and maintain core libraries and runtime applications.
• Integrate classical and geometric methods in computer vision with ML methods.
• Work with ML and Data Infra team to construct various benchmarks for analyzing system performance.

REQUIRED QUALIFICATIONS

• MS or PhD in Machine Learning, Robotics or Computer Science, with emphasis on Computer Vision.
• BS in Computer Science, Machine Learning, Electrical Engineering, or related field.
• 4+ years experience developing and benchmarking ML algorithms on large-scale datasets.
• High proficiency in C++ development in a Linux environment.
• Experience deploying models with TensorRT and ONNX.
• Experience with Python development and deep learning frameworks such as PyTorch and TensorFlow.
• Experience writing and maintaining automated continuous integration tests.
• Experience in one or more of the following:
• Object Detection, Object Tracking, Instance Segmentation, Semantic Segmentation, Semantic change Detection.
• Experience in one or more of the following:
• Visual Odometry, SLAM, Multi-view Geometry, Structure from Motion, 3D Geometry, Discriminative Correlation Filters, Stereo, Neural 3D Reconstruction, RGB-D and LIDAR Sensor Fusion.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Experience troubleshooting and analyzing remotely deployed software systems.
• Proficient in Python.
• Proficient in CUDA.

WHAT YOU’LL DO

• Design and implement algorithms and techniques for RADAR systems
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Guide DSP engineers in the execution of RADAR-DSP trade studies and optimization of signal processing and machine learning algorithms for deployment on FPGAs and GPUs.
• Participate in laboratory and field testing of RADAR-EW systems and techniques
• Participate in the maturation of RADAR-EW systems into deployable systems and products

REQUIRED QUALIFICATIONS

• Experience with Electronic Warfare systems.
• Experience with DSP algorithms and technique development for RADAR- Electronic Support Measures (ESM) and Electronic Counter Measure (ECM) systems.
• Strong experience with DSP implementation for embedded devices and/or software defined radios.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Strong knowledge of Python and MATLAB.
• Excellent at balancing multiple projects at any given time and/or managing a larger team for a larger program.
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Some travel required.
• Currently possesses and is able to maintain an active U.S. Secret/Top Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields.
• Experience with CUDA or GPU accelerated frameworks like cuSignal.
• Familiar with deep learning algorithms. Experience with ML frameworks such as TensorFlow and PyTorch is a plus.
• Experience with embedded devices, including FPGA, Nvidia Jetson, and Software Defined Radios.
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation.

ABOUT THE TEAM

Anduril Maritime delivers platforms, systems, and integrated effects in the maritime domain. Our autonomous vehicles (sub-surface and surface) are the cornerstone of these capabilities, and we continually strive to push the boundaries of the possible in terms of endurance, autonomy and mission capability. The Maritime team develops and maintains core products and payloads, and adapts and applies those products to serve a wide variety of defense, IC and commercial customers in US and international markets.

ABOUT THE JOB 

We are seeking a Senior Machine Learning/MLOps Engineer to join the Applied Intelligence team within Maritime Digital Production. You will lead the design, deployment, and sustainment of the AI-enabled backbone that connects data, tools, and people across our digital shipbuilding environment. This role focuses on operationalizing advanced models and architecting the industrial AI stack—selecting, integrating, and standardizing technologies that bring intelligence into production systems only where they deliver real value.

You’ll define and implement core components of the platform, including unified data and feature stores, vector databases, orchestration layers, and model-serving frameworks, while integrating off-the-shelf models for computer vision, OCR/IDP, speech, and retrieval-augmented generation. You’ll work across software, data, manufacturing, and corporate technology teams to translate real factory scenarios—inspection, root-cause analysis, receiving workflows, scheduling—into applied AI capabilities with clear human-in-the-loop controls, auditability, safety gates, and integrations with PLM, MES, CMMS, ERP, and the unified data plane.

This role demands technical range, judgment, and an instinct for when AI is the right tool versus when a simpler logic or workflow solution wins. You’ll collaborate across Anduril in a high-tech, fast-paced culture of innovation focused on delivering systems that work in the real world. If you want to shape how AI becomes a practical, reliable tool for production and logistics at scale, you’ll be helping build the future of digital shipbuilding and the next generation of maritime vehicles.

WHAT YOU’LL DO 

• Architect and own the AI/ML platform stack—from data ingestion, labeling, and feature engineering to model training, deployment, monitoring, and lifecycle management.
• Select, prioritize, and standardize industrial AI components including feature stores, vector databases + RAG, OCR/IDP and CV/STT providers, orchestration layers, and observability systems.
• Build model-serving and inference frameworks optimized for production environments, supporting real-time and batch execution across cloud, edge, and shop-floor systems.
• Translate factory scenarios (receiving, inspection, RCCA, scheduling) into applied AI workflows with defined human-in-the-loop gates, audit trails, and integration contracts with PLM, MES, CMMS, ERP, and the unified data plane.
• Implement event-driven data pipelines and telemetry systems that feed models with contextualized, real-time signals from production and logistics systems.
• Drive make/buy strategy by researching internal and vendor AI capabilities and recommending investments aligned to enterprise roadmaps, Anduril IP principles, and production constraints.
• Define and maintain model governance processes for validation, safety reviews, traceability, and rollback.
• Partner with Maritime platform teams and CorpTech to align architectures with enterprise data standards, ontologies, and compliance policies.
• Lead reliability engineering for deployed models—managing drift detection, retraining triggers, alerting, and operational SLOs.
• Mentor junior engineers and data scientists; establish best practices for MLOps, observability, data management, and secure handling of sensitive production data.

REQUIRED QUALIFICATIONS 

• Strong stakeholder management skills with proven experience aligning engineering, data, and manufacturing teams.
• 8+ years of experience in software or ML engineering with end-to-end delivery of production-grade AI/ML systems.
• Deep experience with MLOps: data acquisition, labeling, curation, pipeline management, model versioning, continuous integration, and model monitoring.
• Strong proficiency in Python and experience with deep learning frameworks (PyTorch, TensorFlow).
• Experience building and deploying containerized ML services using Docker and Kubernetes.
• Proficiency in data engineering, time-series data modeling, and working with semantic/ontology-driven data systems.
• Experience implementing observability for model performance, inference accuracy, and data drift.
• Familiarity with event-driven architectures, IoT/UNS patterns, and real-time systems integration.
• Excellent communication and documentation abilities; able to bridge research, platform, and production domains.
• Eligible to obtain and maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS 

• Experience applying AI/ML within manufacturing, logistics, industrial control, or production environments.
• Background with digital twins, predictive maintenance, OCR/IDP, CV, or STT model integrations.
• Experience with workflow/orchestration tools such as Flyte, Airflow, Kubeflow, or Temporal.
• Familiarity with GPU acceleration (CUDA) and inference optimization (TensorRT, Triton).
• Experience in regulated environments (NNPI/ITAR) and secure model/data governance.
• Demonstrated ability to mentor engineers and set technical direction for AI/ML infrastructure at scale.

WHAT YOU’LL DO

• Design, develop, and optimize digital signal processing (DSP) algorithms and systems for radio direction finding and direction-of-arrival (DoA) estimation in defense applications.  
• Collaborate with a multidisciplinary team of software and hardware engineers to develop software defined radios; and direct DSP team in the engagement with the software & hardware team, including the implementation of DSP techniques into software and firmware and integration activities.
• Implement high-performance, real-time signal processing chains on embedded and hardware platforms to support mission-critical sensing capabilities.  
• Develop Modeling and Simulation (M&S) code for RADAR techniques and data analysis including Hardware-in-the Loop / Software-in-the-loop (HIL/SIL) testing
• Participate in laboratory and field testing of RF systems and techniques
• Participate in the maturation of RF systems into deployable systems and products

REQUIRED QUALIFICATIONS

• 5+ years with a BSEE or related field
• Strong foundation in digital signal processing, comms theory, & system engineering with emphasis in direction finding algorithm implementation
• Hands-on experience with direction finding, angle-of-arrival estimation, and multi-antenna signal processing.  
• Strong experience with DSP implementation for embedded devices including FPGA, Nvidia Jetson, and Software Defined Radios and/or software defined radios.
• Strong knowledge of Python and MATLAB. Experience with CUDA or GPU accelerated frameworks like cuSignal is preferred.
• Skilled with Modeling and Simulation of RF systems including Radar and SAR
• Familiar with deep learning algorithms. 
• Familiar with wireless communication standards (Bluetooth, 3G/4G/5G, Wi-Fi, SINCGARS, MUOS, etc.).
• Enthusiastic about both working with a team and executing some work individually (depending on program scope).
• Experience with Electronic Warfare systems.
• Currently possesses and is able to maintain an active U.S. Secret security clearance.

PREFERRED QUALIFICATIONS

• Masters or PhD degree in Electrical, Electronics, Computer Engineering, or related fields
• Experience with ML frameworks such as TensorFlow and PyTorch 
• Defense, national security, or aerospace domain familiarity through industry or education.
• Extensive Digital Signal Processing (DSP) knowledge and experience
• Expertise in Synthetic Aperture Radar (SAR) and/or Inverse SAR (ISAR): Image formation, waveforms, phenomenology, modeling and simulation

Why You'll Love This Role

You will work closely with the founding team and a group of highly-skilled engineers to shape the future of AI-enabled Security/Observability platforms. You will play a central role in bringing integrating cutting-edge AI/ML technologies to the Cribl Product suite to help solve real customer problems.  You will work closely with development partners and key stakeholders to iteratively design, develop, and deliver products and surfaces that will delight our customers.

On top of it all you will have fun. Cribl strives to be a great place to work for everyone.

As An Active Member Of Our Team, You Will...

• Design, train, and evaluate machine learning models across a range of research and applied AI initiatives
• Run rapid, iterative experiments to test hypotheses and surface insights that drive model improvements
• Collaborate closely with researchers and engineers to translate cutting-edge academic advances into practical, production-ready systems
• Build and maintain robust ML pipelines for data ingestion, feature engineering, model training, and evaluation
• Optimize model performance through fine-tuning, hyperparameter search, and architecture experimentation
• Contribute to a culture of rigorous experimentation; tracking results, documenting findings, and sharing learnings with the broader team
• Stay current with the latest developments in ML and AI research, and proactively identify opportunities to apply them
• This position may require stand-by, on-call, or off-hours duties during critical research or deployment milestones

If You've Got It - We Want It

• Bachelor's degree in Computer Science, Mathematics, Statistics, or a related field with 5+ years of industry or research experience (Master's or PhD a plus)
• Deep hands-on experience training and evaluating ML models, including language models
• Strong proficiency in Python and ML frameworks such as PyTorch or TensorFlow
• Familiarity with MLOps tooling and infrastructure (e.g., MLflow, Weights & Biases, Kubeflow, or similar)
• Solid understanding of modern NLP, computer vision, and/or reinforcement learning techniques
• Strong ability to move fast without sacrificing rigor; you know when to prototype and when to productionize
• Excellent communication skills with the ability to clearly present experimental results to both technical and non-technical stakeholders

Salary Range ($230,000 - $275,000)

The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate’s job-related knowledge, skills, and experience.  In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus.

#LI-JB1
#LI-Remote

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. 

What You Will Learn:

• Real-world ML benchmarking workflows from model to hardware.
• Performance tuning and optimization techniques.
• How ML applications are tested, validated, and productized.
• Collaboration across software, hardware, and research teams.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders.

This role is hybrid, based out of Santa Clara, CA.  

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.”
• You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life.
• You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon.
• Work directly with customers in meetings, presentations, and workshops to understand their technical challenges and provide effective solutions.
• Partner closely with sales operations and product teams to provide feedback from customers and help shape future product enhancements.

What We Need

• Strong customer-facing skills with 5+ years of relevant technical, enterprise experience (such as Sales Engineer, Solutions Engineer, or Technical Account Manager).
• Your field insight will help shape our roadmap, our features, and the way we show up for developers.
• Proven expertise in AI technologies and frameworks, including machine learning, deep learning, natural language processing (NLP),computer vision, PyTorch or TensorFlow.
• Experience with embedded systems, FPGA Architecture or AI accelerators. Familiarity with hardware/software co-optimization is often critical for efficient inference at the edge.
• Good understanding of data center, server architecture and deployment, thermal/power, and infrastructure management.

What You Will Learn

• How to explore and push the boundaries of AI performance on custom silicon and help developers do the same.
• What it’s like to build the future from scratch, working alongside teams creating hardware, software, and everything in between.
• To master the craft of fine-tuning LLMs, optimizing vision models, and building AI pipelines that run at scale.
• An understanding of why field roles drive real impact turning on-the-ground insight into product breakthroughs and platform momentum.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Join the team revolutionizing AI computing at Tenstorrent. You'll work on TT-Forge, our MLIR-based compiler that enables developers to run AI on all configurations of Tenstorrent hardware using an open-source, performant, and general-purpose compiler. You will be at the forefront of the AI hardware revolution, building compiler technologies that redefine what’s possible.

 This role is hybrid, and can be based out of Santa Clara, CA; Austin, TX; or Toronto; ON.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who You Are

• A passionate software engineer eager to work on compiler technologies and the challenges of AI hardware, whether from compilers, systems, or broader software backgrounds.
• Fluent in C++ and Python, with experience building complex systems that bridge high-level frameworks to low-level execution.
• Excited by compiler optimization and machine learning, with experience in PyTorch, JAX, TensorFlow, or deep systems programming.
• A collaborative problem-solver who thrives in open-source and enjoys working closely with hardware and software engineers.

What We Need

• A drive to solve novel challenges in AI compilation, from optimizing computational graphs to creating custom dialects and transformation passes.
• Experience or strong interest in MLIR and how modular compiler frameworks connect AI models to advanced hardware.
• Motivation to build technology that impacts the future of AI, knowing your work will enable the next wave of breakthroughs.

What You Will Learn

• How to build open-source compiler frameworks supporting diverse AI models and workloads, including training and multi-chip scaling.
• Deep expertise in compiler technologies including custom MLIR dialects (TTIR, TTNN, TTKernel) and transformation passes.
• New methods for human-in-the-loop compiler optimization using TT-Explorer, making advanced tuning tools usable by all developers.
• How compiler technology powers Tenstorrent’s mission to deliver affordable, open-source AI computing in a highly competitive space.

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

Tenstorrent is seeking an Physical Design Engineer to lead  cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. 

This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO.

We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.

Who you are

• BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes.
• Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs.
• Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows.
• Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.

What we need

• Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes.
• Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly.
• Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR.
• Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.

What you will learn

• How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows.
• New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits.
• Best practices for deploying, validating, and monitoring ML models in production CAD environments.
• How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).

Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made.

Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer.

This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. 

About the role

At Applied Intuition, you will:

• Develop, integrate, and adapt cutting-edge AI/ML algorithms running on the perception autonomy stack to collect relevant information across a suite of platform sensors
• Create interfacing software to autonomously control sensors (e.g., EO, IR, acoustics, radar, and RF)
• Collaborate across the sensor, tracking, and autonomy teams to ensure seamless deployment of heterogeneous platform swarms in on-site DoD testing and demonstration events
• Deploy containerized solutions to embedded Linux devices, leveraging computer-in-the-loop testing and profiling, and efficiently collecting performance data
• Interact with the DoD customer to understand their use cases, requirements, and triage needs during field events to deliver a superior customer experience
• Work closely with our existing team to internally triage technical problems and scope
• Carefully communicate and document ongoing work to ensure internal flexibility in a fast paced environment as well as clarify progress with external customers
• Drive execution of simulation tooling to playback sensors, platforms, and autonomy in post processing field test analysis
• Implement improvement plans for future integration efforts based on simulation analysis and customer feedback

We're looking for someone who has:

• MS or PhD in Electrical Engineering, Computer Engineering, Robotic Engineering, Computer Science, Optimization, or equivalent OR 5+ years of relevant experience working with sensor algorithms, hardware, and HIL software integration
• Experience with multiple sensor modalities (e.g., EO, IR, lidar, radar, sonar, acoustics, etc.)Core understanding of sensor physics and sensor control parameters
• Experience training and deploying ML algorithms (python, pytorch, tensorflow) onto integrated systems (onnx, C++ models)
• Familiarity with tracking basics (e.g., Kalman filters) and optimal sensor fusion
• Experience working comfortably in Linux and Docker
• Prior experience with remote software development, ability to handle and process large datasets, and learn new software and algorithms as needed with little supervision

Travel Requirements:

• Must be willing to travel as projects requires, usually for SW/HW integration and/or demonstrations; estimated average travel is every 1-2 months for 2-5 days (10-20%)
• Travel-adverse candidates are encouraged to inquire about relocation assistance to HQ in Poway, CA

Security Requirements:

• Must be a U.S. Citizen
• Must hold or be eligible to obtain and maintain a U.S. security clearance

For more information about U.S. security clearances: click here.

Nice to have:

• Proficiency with modern C++ development (2011, 2017, 2020, smart pointers, etc.), CMAKE, Python and Bash
• PhD in computer science or electrical engineering with AI/ML focus
• Experience with robotic swarm or multi-agent systems and optimization   
• Strong tracking and sensor fusion background
• Current U.S. SECRET security clearance

Compensation at Applied Intuition for eligible roles includes base salary, equity, and benefits. Base salary is a single component of the total compensation package, which may also include equity in the form of options and/or restricted stock units, comprehensive health, dental, vision, life and disability insurance coverage, 401k retirement benefits with employer match, learning and wellness stipends, and paid time off. Note that benefits are subject to change and may vary based on jurisdiction of employment.

Applied Intuition pay ranges reflect the minimum and maximum intended target base salary for new hire salaries for the position. The actual base salary offered to a successful candidate will additionally be influenced by a variety of factors including experience, credentials & certifications, educational attainment, skill level requirements, interview performance, and the level and scope of the position.

Please reference the job posting’s subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the location listed is: $140,000 to $220,000 USD annually.

About the Role

We're seeking an exceptional Senior Engineering Leader to build and lead a high-performing engineering team focused on design and development of a distributed multi-tenant AI inference SaaS platform. Platform development responsibilities include but are not limited to software design, development and testing for multiple domains such as inference engines (AI/ML, program and compiler analysis), core platform services, and observability. This role sits at the intersection of systems engineering, AI/ML operations, and product development, requiring both deep technical expertise and proven leadership capabilities.

As a leader at Gruve, you'll drive the technical vision and execution of critical infrastructure that enables our AI capabilities at scale. You'll work closely with cross-functional partners including research scientists, product managers, and other engineering leaders to deliver robust, performant systems that power our AI products.

This position is based in the United States and reports to the SVP of Inferencing and Infrastructure Management

Key Responsibilities

• Team Leadership & Development: Build, mentor, and scale a world-class engineering team of 10-15+ engineers. Foster a culture of technical
• Excellence, collaboration, and continuous learning. Conduct performance reviews, career development planning, and succession planning.
• Technical Strategy & Architecture: Define and execute the technical roadmap for AI inference infrastructure, AI toolchains, and AI software development. Make critical architectural decisions that balance performance, scalability, maintainability, and cost.
• Compiler Design & Optimization: Lead the development of AI inference systems and optimizations for AI workloads, including graph optimization, kernel fusion, and hardware-specific code generation to maximize inference performance.
• AI Model Development & Deployment: Oversee the end-to-end lifecycle of AI models from development through production deployment, including model fine-tuning, quantization, distillation, and serving infrastructure.
• Inference API & Platform Development: Drive the design and implementation of scalable, low-latency inference APIs and platforms that serve models reliably at production scale with strict SLA requirements.
• Spec-Driven Development: Champion rigorous engineering practices including comprehensive technical specifications, design reviews, and documentation to ensure alignment and quality across complex projects.
• Cross-Functional Collaboration: Partner effectively with research, product, and business stakeholders to translate requirements into technical solutions and communicate progress, trade-offs, and risks clearly.
• Delivery & Execution: Own quarterly planning, roadmap prioritization, and on-time delivery of major initiatives. Establish metrics and KPIs to measure team performance and system health.

Basic Qualifications

• 10-15+ years of software engineering experience with at least 5+ years in engineering leadership roles managing teams of 5+ engineers
• Proven track record of building and scaling high-performing engineering teams in high-growth technology companies
• Deep expertise in systems programming languages (C++, Go, Rust, or similar) and architecture design
• Strong background in AI model design, optimization, or adjacent systems-level programming (LLVM, MLIR, XLA, or similar frameworks)
• Hands-on experience with AI/ML model development, training, and inference systems
• Experience with model fine-tuning techniques and deployment optimization (quantization, pruning, etc.)
• Demonstrated ability to design and build production-grade APIs and distributed systems
• Strong understanding of spec-driven development processes and engineering best practices · Excellent communication skills with ability to influence across all levels of the organization
• Demonstrated ability to work effectively with teams across multiple time zones
• Bachelor's degree in Computer Science, Engineering, or related technical field (or equivalent practical experience)

Preferred Qualifications

• Master's or PhD in Computer Science, Machine Learning, or related field
• Experience at leading AI/ML companies or research labs (OpenAI, Google DeepMind, Meta AI, Anthropic, etc.)
• Direct experience with modern ML frameworks (PyTorch, JAX, TensorFlow) and their compilation stacks
• Background in GPU programming (CUDA, Triton) and hardware acceleration for ML workloads
• Experience with transformer architectures and large language model (LLM) inference optimization
• Track record of shipping production ML systems serving millions of requests per day
• Contributions to open-source compiler or ML infrastructure projects
• Experience with cloud infrastructure (AWS, GCP, Azure) and containerization/orchestration (Kubernetes, Docker)
• Previous experience scaling teams from <10 to 20+ engineers

Salary Range 

$240,000 - $300,000 USD + Benefits

This position is with Gruve and is an on-site role based at the Gruve headquarters in Redwood City, California.

‍

Who we are

Neros is a defense technology company rebuilding America’s drone industrial base. We design and manufacture high-performance unmanned systems that are tested in combat, iterated at startup speed, and built at massive scale. Our team culture is fast, hands-on, and obsessed with closing the gap between design and deployment.

As drones transform the character of warfare, Neros is delivering the systems the West needs to compete on the modern battlefield and deter the adversaries of democracy. We’re hiring engineers, operators, and builders who want to move fast, take on extreme ownership, and get capability into the hands of warfighters in months, not years.

What you will be doing

The Autonomy Computer Vision Engineer will be responsible for developing and implementing cutting-edge computer vision algorithms to be deployed onboard Neros drones. This role involves designing, testing, and optimizing algorithms for real-time operation in autonomous systems, ensuring high performance and reliability in diverse environments. The candidate will collaborate closely with cross-functional teams, including robotics engineers, software developers, and hardware engineers, to integrate vision-based solutions into autonomous drone platforms.

You should have the following

• 3+ years of experience in computer vision, robotics, or related fields
• Proven experience in developing algorithms for real-time systems, preferably for autonomous platforms
• Strong proficiency in programming languages such as Python and C++
• Expertise in computer vision libraries and tools like OpenCV, TensorFlow, PyTorch, or similar
• Experience with SLAM, object detection, and image segmentation techniques
• Familiarity with UAVs and drone systems
• Knowledge of real-time system constraints
• Proficiency in debugging, testing, and validating algorithms in simulation and real-world environments

US Salary Range

$150,000 - $200,000 USD

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are considered part of Neros' total compensation package.

We’re an equal opportunity employer. We welcome all applicants without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.

Shopmonkey's vision is to help every shop thrive by equipping them with the tools they need to run and grow their business. Our cloud based all-in-one shop management software takes owners and technicians from quote to cashing out a satisfied customer. Our software has a modern and intuitive UI and our backend is powered by the latest technologies so our clients can focus on the things they do best. As a Senior ML Engineer at Shopmonkey, you will be a part of a globally distributed engineering team working closely with your product and design counterparts. You will have the chance to work on the frontier of ML modeling, data pipelines, MLOps, and agentic AI systems to meet real-world auto shop needs. Shopmonkey has the structured data, workflows, and operational maturity to deliver ML powered systems that are not only intelligent but trusted and useful. You’ll move fast to bring ML systems from discovery all the way through production, helping to shape the future of the automotive care experience. For any Bay area based candidates, this would be hybrid with 2-3 days/week office at our Morgan Hill, CA office for collaboration. 

What you will do:

• Design, build, and ship production-ready ML models across a range of problem spaces: regression, classification, clustering, ranking, and recommendation systems.
• Conduct end-to-end development of ML systems: data gathering, experimentation, feature engineering, model training, evaluation, deployment, and monitoring.
• Define and track model performance metrics, run A/B tests, and iterate based on real-world feedback.
• Help design and implement shared feature stores so that reusable features can serve multiple models consistently in both batch and real-time contexts.
• Work within a modern MLOps environment to ensure scalable and reliable deployment of models.
• Contribute to training infrastructure, model versioning, and CI/CD pipelines for ML workflows.
• Work closely with data scientists and data engineers to develop data driven solutions that are high impact for businesses.
• Translate complex ML workflows into digestible updates for cross-functional stakeholders.
• Contribute to backlog velocity by owning appropriate tickets and delivering high-impact work in a collaborative, fast-paced environment.
• Implement NLP and LLM-powered components for sentiment analysis, real-time conversation evaluation, and behavior optimization.
• Contribute to analytics and predictive features such as no-show prediction and sentiment dashboards.
• Help build and ship AI agents that help automate key auto-shop business processes.

We are looking for people who have:

• Minimum of 5+ years of industry experience in applied machine learning; advanced degrees (Master’s or PhD) may offset years of experience.
• Proven experience shipping models into production (not just proof-of-concepts or notebooks).
• Proficiency in Python; experience with ML frameworks like PyTorch or Tensorflow.
• Strong foundations in classical ML/DL. Including some of the following: regression, classification, clustering, ranking, feature engineering, model evaluation, and experimentation.
• Bachelor’s degree in a STEM field, or equivalent practical experience.
• Strong collaboration and communication skills—comfortable working with PMs, designers, engineers and other cross functional team members.

Nice to have:

Candidates should have some experience in one or more of the following areas.

• Understanding of MLOps principles: model versioning, orchestration, evaluation, monitoring, model serving, and CI/CD for ML. 
• Understanding of MLOps, and experience with modern tooling like MLFlow, DVC, Airflow, etc.
• Experience with LLMs and NLP frameworks (e.g., TensorFlow, Hugging Face, LangChain).
• Experience with/interest in LLM workflows and agentic workflows
• Cloud infrastructure experience, (e.g. GCP, AWS).
• Familiarity with vector databases (e.g. Pinecone, pgvector) and embedding-based retrieval or similarity search.
• Strong SQL skills for working with large-scale data.
• Experience designing or contributing to feature stores (e.g. Feast, VertexAI Feature Store, Tecton) for shared, reusable feature pipelines.

Bonus Points:

• Prior experience working at a high growth startup.
• Experience building consumer-facing agents in vertical SaaS, in the automotive industry (business or consumers).
• Background in data processing or real-time analytics.
• Experience with Snowflake or other large-scale data warehouse solutions.

In the United States, the range is typically a salary of $165,000 to $200,000 + bonus + equity + benefits. The range provided is Shopmonkey’s reasonable estimate of the base compensation for this role. The actual amount will be based on job-related and non-discriminatory factors such as location, experience, training, skills, and abilities. Consult with your Recruiter during the initial call to determine a more targeted range based on these job-related factors. In addition to this base compensation company stock options and benefits as outlined below are included.

Please note that this position can be based in Princeton, NJ. Acadia's hybrid model requires this role to work in our office three days per week on average.

Position Summary

Primary Responsibilities

• Design, develop, validate, and deploy machine learning, statistical, and GenAI solutions that address complex business problems and support enterprise priorities
• Contribute to execution of the enterprise AI strategy and roadmap by providing technical input on use‑case feasibility, value hypotheses, architecture decisions, and build‑vs‑buy assessments
• Build and maintain scalable ML and LLM pipelines from data ingestion through production, adhering to established ML Ops and LLM Ops standards including versioning, evaluation, observability, and rollback
• Partner with business, analytics, IT, and security teams to identify, prototype, and deliver high‑value AI use cases across the organization
• Evaluate and integrate AI and GenAI platform components such as model endpoints, vector databases, agent frameworks, and guardrails in alignment with enterprise architecture standards
• Contribute to AI governance by supporting model documentation, lineage, risk assessment, bias testing, explainability, and compliance with applicable regulations and frameworks
• Provide technical input into AI platform and vendor evaluations, including RFI/RFP activities and assessments of cost, security, and data residency
• Support AI enablement efforts through development of reusable patterns, reference implementations, and technical documentation to accelerate adoption
• Apply and uphold policies for AI lifecycle management, bias/robustness testing, explainability, human oversight, and incident response. Support mapping of AI controls to major frameworks and regulations (e.g., NIST AI RMF, EU AI Act readiness) to ensure responsible and compliant AI deployment.
• Ensure all data science work complies with global AI regulations, ethical standards, and applicable GxP processes.
• Participate in cross-functional AI Governance Council activities as requested, providing technical expertise on model risk and data science practices.
• Other duties as assigned

Education/Experience/Skills

• Master’s degree or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative discipline, or equivalent practical experience
• 5+ years of hands‑on experience in applied data science and machine learning, including model development, deployment, and production support
• Advanced proficiency in Python and common ML frameworks and tools such as scikit‑learn, TensorFlow, PyTorch, and SQL
• Practical experience with ML Ops and LLM Ops practices including model registries, version control, evaluation benchmarks, and monitoring
• Experience working with large language models, GenAI technologies, vector databases, or agent frameworks
• Experience operating in a regulated environment and following GxP or similar compliance processes
• Willingness and ability to travel domestically and internationally

Physical Requirements

This role involves regular standing, walking, sitting, and the use of hands for handling or operating equipment. The employee may also need to reach, climb, balance, stoop, kneel, crouch, and maintain visual, verbal, and auditory communication in a standard office environment and while working independently from remote locations. The employee must occasionally lift and/or move up to 20 pounds.  This position requires the ability to travel independently overnight and/or work after hours as required by travel schedules or business needs.

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#LI-CS1

Make your impact within a rapidly growing Fintech Company

Join BILL's AI Product Engineering team and help shape the future of intelligent financial automation. As a Senior Machine Learning Engineer, you'll play a pivotal role in designing, building, and deploying machine learning solutions that power BILL's next-generation products. This is an opportunity to work in a collaborative, high-impact environment where your expertise will directly influence the company's growth and the experience of millions of users.

Responsibilities:

• Design, develop, and deploy robust machine learning models to solve real-world business challenges in the fintech domain
• Collaborate cross-functionally with product managers, engineers, and data scientists to translate business requirements into scalable ML solutions
• Analyze complex datasets, identify patterns, and extract actionable insights to drive product innovation
• Evaluate, optimize, and monitor model performance in production, ensuring reliability and accuracy over time
• Contribute to the development and improvement of AI workflows, agentic evaluation and best practices within the team
• Document methodologies, experiments, and results to ensure knowledge sharing and reproducibility
• Mentor junior team members and share technical expertise to elevate team capabilities

We’d love to chat if you have:

• Proven experience building and deploying machine learning models in production environments
• Strong programming skills in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Previous experience with OCR extraction and NLP methodologies
• Knowledge of AI agents and strong experience with LLMs
• Ability to analyze and interpret large, complex datasets using statistical and data analysis techniques
• Excellent communication and collaboration skills, with a track record of working effectively in cross-functional teams
• A problem-solving mindset and a passion for continuous learning and innovation

Visa Sponsorship:  Please note that this position is eligible for visa sponsorship. 

#LI

OPEN POSITION ANNOUNCEMENT!

Data Engineer

Open until filled.

Posted 4/29/2026 San Diego County – hybrid work schedule set by SDCP

About the role:  The San Diego Community Power (SDCP) is seeking a seasoned Data Engineer to join our growing team of analytics experts who will be responsible for designing, maintaining, expanding, and optimizing our data infrastructure for data collection, management, transformation, and access. A key priority of this role will be to assist in SDCP’s development of centralizing its data eco-system to allow for creation of pipelines that convert raw data into usable formats for data analysts and other data consumers to utilize. The Data Engineer will handle the core data aspects of software engineering and data science and utilize software engineering principles to develop algorithms that automate the data flow process. They will collaborate with data and system analysts to build machine learning and analytics infrastructure from testing to deployment. 

WHO IS SAN DIEGO COMMUNITY POWER?

San Diego Community Power is a community-driven, not-for-profit public agency providing cleaner energy to the San Diego region. Formed in 2019, Community Power is the second largest Community Choice Aggregator (CCA) in California, serving nearly 1 million customer accounts across its member agencies: the Cities of San Diego, Chula Vista, Encinitas, Imperial Beach, La Mesa and National City, as well as the unincorporated areas of San Diego County.  

OUR HISTORY

San Diego Community Power was formed in 2019 as a public, not-for-profit community choice aggregator (CCA) in the San Diego region. We began electric service in 2021 and serve five member agencies: San Diego, Chula Vista, Encinitas, La Mesa and Imperial Beach, County of San Diego, and National City. SDCP was formed to bring local control and customer choice to San Diego while also providing clean and renewable energy at competitive rates. By the end of 2023, SDCP will provide electricity for nearly half the electric load in San Diego Gas and Electric’s service territory and will be the second largest CCA in California. For more information, please visit SDCommunityPower.org.

COMMITMENT TO DIVERSITY

At SDCP, we value diversity and are committed to creating an inclusive environment for all employees. We represent a diverse customer base and hope to hire employees that reflect our communities. We provide equal employment opportunities to all applicants for employment and prohibit discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. 

ESSENTIAL DUTIES AND PRIMARY RESPONSIBILITES

• Building and maintaining a centralized cloud-based data infrastructure for optimal extraction, transformation, and loading of data from a wide variety of sources. 
• Assemble large, complex data sets that meet functional/non-functional business requirements. 
• Developing data tools and APIs for data analysis. 
• Deploying and monitoring machine learning algorithms and statistical methods in production environments to solve organizational needs. 
• Ensuring data accessibility and security and implementing company data policies regarding data privacy and confidentiality. 
• Improving data systems reliability, speed, and performance. 
• Build analytics tools that utilize the data pipeline to provide actionable insights into customer trends, operational efficiency, and other key business performance metrics. 
• Collaborating with other internal teams, data analysts, and other stakeholders to understand and optimize how data can be leveraged to meet business needs. 
• Assist in drafting data and analytics’ solicitations and in the selection of consultants. 
• Assist with drafting staff reports and presentations for Board and Committee meetings. 
• Performs other related duties and responsibilities as required. 

MINIMUM KNOWLEDGE, SKILLS, AND ABILITES

• Advance working knowledge of SQL, experience working with relational databases, query authoring (SQL) and working familiarity with various databases. 
• Demonstrated experience in developing API and integrations to support analytics in cloud environment. 
• Experience building and optimizing ‘big data’ data pipelines, architectures, and data sets. 

• Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement. 
• Strong analytic skills related to working with unstructured datasets. 
• Build processes supporting data transformation, data structures, metadata, dependency, and workload management. 
• A successful history of manipulating, processing, and extracting value from large, disconnected datasets. 
• Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores. 
• Good understanding of data architecture, data design, data warehousing and data modeling concepts. 
• Strong project management and organizational skills. 
• Experience supporting and working with cross-functional teams in a dynamic environment. 

PREFERRED KNOWLEDGE, SKILLS, AND ABILITES

• Experience in the energy sector and/or supporting the implementation of programs funded by California state agencies (e.g., California Public Utilities Commission, California Energy Commission, California Air Resources Board).
• Ability to strongly represent the organization in various professional engagement settings from local to national convenings (conferences, workshops, executive meetings, etc.).

PREFERRED QUALIFICATIONS, EDUCATION AND EXPERIENCE

Minimum of two (2) to three (3) years of professional experience in a Data Engineer role, preferably in the energy industry with a graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. The candidate should also have experience using the following software/tools:

• Experience with big data tools: Hadoop, Spark, PowerBI, Kafka, etc.
• Experience with AWS, Azure and Google Cloud services.
• Experience with relational SQL and NoSQL databases.
• Experience with data pipeline and workflow management tools: Azkaban, Luigi, Airflow, etc.
• Experience with open-source technologies: Python, Pytorch, Flask, Tensorflow or Keras
• Experience with stream-processing systems: Storm, Spark-Streaming, etc.
• Experience with object-oriented/object function scripting languages: Java, C++ etc.
• Experience with batch, micro-batching and real-time data ingestion methodologies.
• Experience with GitHub or similar code repositories

WORK ENVIROMENT & CONDITIONS

Prolonged periods sitting at a desk and working on a computer. The position requires occasional carrying, lifting and/or moving objects up to 25 pounds. Occasional local travel required and reliable transportation to be able to attend SDCP events, meetings, and workshops as needed is expected. At SDCP we work in the communities we serve and in the office. SDCP works to ensure a safe and healthy workplace for employees and in our communities. SDCP requires employees to be fully vaccinated for COVID-19. SDCP is an agency required to adopt and promulgate a Conflict-of-Interest Code (“COI”). The COI code requires employees in designated positions, including those identified under the interim disclosure process to file a Statement of Economic Interests (Form 700) on an annual basis. A Successful candidate accepting this position may be required to file Conflict of Interest forms subject to the regulations of the Fair Political Practices Commission.

COMPENSATION: 

Salary Range: The position salary range is: $84,900 - $110,400; with exact compensation to be determined by SDCP, depending upon experience. 

Benefits: Standard benefits package including but not limited to:

Insurance: SDCP offers group health benefits, including medical, vision, and dental insurance, for eligible FT employees. Also provided is a $100,000 Life & AD&D policy, STD and LTD coverage that is 100% paid by SDCP.

Retirement: SDCP offers a 457(b) plan for employee contributions and contributes 10% of eligible compensation to the employee’s Money Purchase Plan.

Paid Time Off: 11 holidays per year + paid winter holiday (between 12/24-12/31), 160 hours of accrued paid time off per year (increases with time in service), and 96 hours per year of accrued paid sick leave.

This job description may not be inclusive of all assigned duties, responsibilities, or aspects of the job described, and may be amended at the discretion of SDCP as needed. 

WHAT YOU’LL DO

THE DAY-TO-DAY

• Lead and Define AI Strategy – Set the vision for applied ML research and AI-driven decision-making across Viant’s products and services.
• Drive High-Impact Research – Conduct advanced research in NLP, RL, LLMs, and deep learning, publishing in top-tier conferences while applying findings to real-world production systems.
• Architect and Deploy ML at Scale – Develop, optimize, and deploy high-throughput, low-latency ML models, collaborating with engineers to bring solutions into production.
• Innovate in Generative AI & Causal ML – Explore novel AI techniques, such as LLMs, reinforcement learning, and causal inference, to enhance targeting, personalization, and attribution models.
• Experimentation and Validation – Design, run, and analyze A/B experiments to test ML-driven strategies, ensuring data-driven decision-making.
• Mentor and Influence – Provide technical leadership for a team of applied scientists and ML engineers, fostering a culture of innovation and excellence.

MUST HAVE

• Experience: 4+ years of experience building and deploying machine learning models at scale.
• Technical Leadership: Demonstrated ability to lead complex, high-ambiguity ML projects from research to production.
• Academic & Industry Recognition: Masters + At least two peer-reviewed publications in deep learning, NLP, or a related AI domain or a PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field.
• Deep Expertise in ML & AI: Strong foundation in deep learning, NLP, generative AI, and causal inference.
• Programming & Frameworks: Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, LangChain, Llama Index).
• Scalability & Cloud: Experience with distributed computing, cloud ML platforms (AWS, GCP, or Azure), and real-time AI inference.

GREAT TO HAVE

• Industry Impact: Publications at top-tier ML/NLP conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, AAAI).
• Ad Tech Expertise: Experience in digital advertising, real-time bidding, or audience modeling.
• Generative AI Applications: Hands-on experience with LLMs and multimodal AI applications.
• Optimization & Personalization: Strong background in reinforcement learning, dynamic pricing, or recommendation systems.

LIFE AT VIANT

Investing in our employee’s professional growth is important to us, but so is investing in their well-being. That’s why Viant was voted one of the best places to work and some of our favorite employee benefits include fully paid health insurance, paid parental leave and unlimited PTO and more. 

#LI-KW1

What We're Looking For

We are looking for a Senior Application Security Engineer to help secure our AI, machine learning, and inference platforms. This is a hands on technical role focused on building security into modern AI infrastructure, inference systems, and developer platforms.

You will work closely with platform engineers, ML engineers, and infrastructure teams to identify risks, design secure architectures, and build security tooling that enables engineers to move quickly and safely.

This role is execution focused. You will drive technical implementation, perform deep security reviews, and help build out our application security capabilities alongside the CISO and engineering leadership.

This role can be based out of one of our office hubs (San Francisco or Seattle) with in-office requirements of at least 2 days per week, plus occasional team/company offsites. We are not able to offer visa sponsorship for this position at this time.

What You’ll Do

Secure AI and Machine Learning Systems

• Perform threat modeling across AI platforms, inference services, and ML pipelines
• Identify risks such as prompt injection, model extraction, adversarial inputs, and data leakage
• Review model serving architectures and inference pipelines
• Partner with ML engineers to secure training, fine tuning, and deployment workflows
• Help design isolation and security controls for multi tenant AI workloads

Application Security Engineering

• Perform architecture and design security reviews
• Conduct targeted code reviews for high risk components
• Identify security gaps in APIs, micro-services, and distributed systems
• Build secure patterns for authentication, authorization, and service to service communication
• Help engineering teams implement secure defaults and guardrails

Inference Platform Security

• Secure customer facing inference APIs and services
• Protect against abuse, model extraction, and adversarial behavior
• Design rate limiting, isolation, and workload protection controls
• Build monitoring and detection for anomalous inference behavior

AI Supply Chain and Model Security

• Evaluate open source models and dependencies
• Secure model artifacts and distribution pipelines
• Implement integrity validation and provenance controls
• Help secure container images and runtime environments

Security Automation and Tooling

• Build security automation for AI and application pipelines
• Integrate security scanning into CI/CD workflows
• Develop tooling to help engineers detect and fix issues early
• Improve developer experience with security guardrails

What You'll Need

Required Experience

• Strong background in application security engineering
• Experience performing threat modeling and architecture reviews
• Experience securing APIs and distributed systems
• Experience working in cloud environments such as AWS, GCP, or Azure
• Experience with containers and Kubernetes
• Strong scripting or programming skills such as Python, Go, or similar
• Experience working closely with engineering teams to implement security improvements

AI and Machine Learning Experience

• Experience securing ML pipelines, inference systems, or data platforms
• Familiarity with risks such as prompt injection, model extraction, and adversarial inputs
• Experience reviewing model serving architectures
• Understanding of training data security and data leakage risks

It's a Strong Plus If You Have

• Red team or offensive security experience
• Experience crafting payloads and evaluating CVEs for exploitability in diverse environments
• Experience with GPU infrastructure or high performance computing
• Experience with Hugging Face, PyTorch, TensorFlow, or similar frameworks
• Experience with LLM systems, RAG pipelines, or agent frameworks
• Experience building security automation pipelines
• Experience securing multi tenant infrastructure

What Success Looks Like

• Security is embedded into AI platform architecture early
• Engineering teams ship quickly with secure defaults
• Inference platforms are resilient against abuse and extraction
• Model pipelines are secure and auditable
• Security tooling scales with engineering growth

Why This Role Matters

This role sits at the intersection of application security, AI infrastructure, and developer platforms. You will help define how we secure modern AI systems while enabling engineers to move quickly and safely.

You will work closely with engineering leadership and the CISO to build practical, scalable security capabilities that support rapid innovation in AI and machine learning.

Compensation

Founded in Silicon Valley in 2009 by Marc Andreessen and Ben Horowitz, Andreessen Horowitz (aka a16z) is a venture capital firm that backs bold entrepreneurs building the future through technology. We are stage agnostic. We invest in seed to venture to growth-stage technology companies, across AI, bio + healthcare, consumer, crypto, enterprise, fintech, games, and companies building toward American dynamism. a16z has $100B+ under management across multiple funds.

We’ve established a team that is defined by respect for the entrepreneur and the company-building process; we know what it’s like to be in the founder’s shoes. We’ve invested in companies like Anduril, Airbnb, Coinbase, Cursor, Databricks, Deel, Figma, GitHub, Roblox, SpaceX, and Stripe. Our team is at the forefront of new technology, helping founders and their companies impact and change the world.

The Role

You will join a team of highly autonomous, senior ICs developing both software capabilities for the firm’s investing and operating functions, and external-facing products for the firm’s partners, portfolio, and investors. This role specifically involves leading the technical strategy, architecture, and implementation of machine learning systems that power the firm’s internal and external-facing applications. You will be responsible for the entire model lifecycle, from feature engineering and training to large-scale, low-latency serving and robust MLOps infrastructure.

The Applied Software Group operates in the mode of an internal startup. We own an exceptionally tight feedback loop and take on requests from all corners of the firm. This is a high-visibility role that requires a clear architectural vision, strong software engineering fundamentals, exacting communication skills, and the ability to engage and educate our firm on the technology we are developing and shipping.

This role requires an in-office presence 2-3 days a week in our San Francisco, CA office.

To join our team, you should be excited to:

• Architect, build, and maintain scalable and reliable ML production pipelines (data, training, and inference)
• Collaborate with the Applied Software Group (ASG) team to integrate ML models into user-facing products serving the investing partnership and our operating teams
• Set and evolve MLOps standards for the team, including producibility, automated testing, CI/CD, observability, and model governance across the firm.
• Research and lead the implementation of model serving strategies (e.g., real-time APIs, batch processing) to meet strict latency and throughput requirements
• Drive the technical roadmap for core ML infrastructure, influencing platform choices and building cloud-native systems primarily on GCP.
• Operate with high autonomy, owning outcomes end-to-end, proactively identifying gaps, and raising the technical bar for the team.
• Set a high standard for code quality and system design, producing clear, principled, and extensible solutions that scale with the firm.
• Bring positive energy in every interaction with the team and foster inclusive collaboration
• Learn the inner workings of VC and work closely with the investing partnership

Minimum Qualifications

• 2+ years of professional experience as a Machine Learning Engineer or similar role.
• Strong mathematical intuition and problem-solving skills
• Expertise in Python and its statistical modeling ecosystem (e.g. NumPy, scikit-learn, etc.)
• Solid experience with major ML frameworks like PyTorch, TensorFlow, or JAX
• Proven experience deploying and managing ML models in a production environment using tools like Kubeflow, MLflow, Airflow, or TFX
• Strong understanding of containerization technologies (e.g., Docker, Kubernetes/GKE) as applied to ML serving
• Familiarity with cloud computing environments (preferably GCP), including data storage and compute services
• Low ego, high empathy, and the capacity to collaborate effectively with diverse teams

The anticipated salary range for this role is between $341,000 - $422,000, actual starting pay may vary based on a range of factors which can include experience, skills, and scope.

This role is eligible to participate in the a16z carry program and various discretionary bonus programs as well as benefit and perquisite plans including health, dental, vision, disability, life insurance, 401K plan, vacation, and sick leave.

About the role

In the role of senior machine learning engineer, you will report to the director of data science and machine learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California.

In this Machine Learning Engineer role focused on Algorithm Development and End-to-End Production at our VOD streaming company, you will lead the creation and deployment of scalable ML models to detect account sharing fraud, drawing from user behavior data like geolocation, concurrent sessions, and device profiles. This position is essential for collaborating with data scientists, product analysts, and data engineers,  translating research prototypes into production systems that enhance detection accuracy while minimizing user disruption, aligning with proven strategies from streaming giants to boost subscriber growth.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. 

Core Areas of Responsibility

• Design and implement machine learning algorithms, including anomaly detection models, to identify unauthorized account sharing in real-time.
• Develop end-to-end ML pipelines for data preprocessing, model training, evaluation, and deployment using cloud platforms.
• Optimize models for performance, scalability, and efficiency to handle high-volume streaming data.
• Integrate ML solutions with existing systems via APIs and establish monitoring for model drift and retraining.
• Collaborate on A/B testing and iteration to refine algorithms based on feedback and evolving evasion tactics.

About You

• Experience: You bring 5+ years of hands-on experience in ML engineering, with a track record in fraud or anomaly detection systems, ideally in online, consumer facing products and services.
• Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or XGBoost, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks MLFlow, etc. Experience with cloud computing infra and tooling such as AWS/GCP.
• Cross-Functional Collaborations: Experienced in working with data scientists, engineers, and product teams to deploy models that support business goals like revenue optimization.
• Communication Skills: Strong ability to document technical processes and explain algorithm decisions to diverse stakeholders for seamless integration.
• Education Background: Possess a master's degree in computer science, machine learning, or a related quantitative field, with certifications in cloud ML being a plus.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Statistics, or a related field.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

About the role

In the role of Senior Machine Learning Engineer for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in the Center for Data and Insights, working from Los Angeles or San Francisco area in California. You will lead the research, development, and test of advanced models, and work together with product and engineering partners to deliver tailored experiences for our fans across the anime ecosystem, including anime video recommendations, digital manga suggestions, merchandise personalization, anime-themed gaming, music, and more. This position will collaborate closely with scientists, engineers, product owners, to prototype innovative algorithms, evaluate their impact, and integrate them into production systems that drive user engagement, retention, discovery, and satisfaction.

We work a hybrid schedule, in-office three days a week; Tuesday, Wednesday, Thursday. This position can be based in our Los Angeles or San Francisco offices.

Core Areas of Responsibility

• Research, design, and implement machine learning algorithms for recommendation systems, including collaborative filtering, content-based models, and deep learning, and generative recommendation approaches to personalize content discoveries.
• Co-develop end-to-end ML pipelines for data ingestion, feature engineering, model training, evaluation, and deployment using scalable cloud platforms with engineers.
• Optimize models for accuracy, latency, and scalability to handle massive user interaction data from streaming and multi-platform, multi-domain experiences across the fandom.
• Integrate personalization solutions with other services, and implement monitoring for model performance, bias detection, and automated retraining.
• Collaborate on A/B testing, experimentation, and iterative improvements to refine recommendations based on user feedback and evolving content trends.

About You

We get excited about candidates, like you, because you have:

Experience: You bring 8+ years of hands-on experience in applied machine learning, with a proven track record in building recommendation systems or personalization engines, ideally in media, entertainment, or e-commerce platforms.

Technical Skills: Expert in Python and frameworks like TensorFlow, PyTorch, or Scikit-learn, with proficiency in MLOps tools such as MLflow, Docker, and cloud services like AWS SageMaker, Databricks, or similar. Experience with big data tools (e.g., Spark) and cloud infrastructure (e.g., AWS/GCP) for handling large-scale datasets.

Cross-Functional Collaborations: Experienced in partnering with data scientists and analysts, engineers, and product teams to deploy models that align with business objectives like increasing user retention and content consumption.

Communication Skills: Strong ability to document research findings, explain algorithmic choices, and present results to diverse stakeholders for effective adoption.

Educational Background: Graduate degree (MS or PhD) in Computer Science, Machine Learning, Statistics, or a related quantitative field, with publications or contributions in recommendation systems being a plus.

About the Team

Our team is composed of passionate Machine Learning Engineers and Data Scientists who have already made a significant impact across our product offerings, content strategy, and user engagement metrics. As we expand our scope, our team is poised to become the cornerstone of innovation and growth across various business verticals within the company. We are dedicated to leveraging advanced machine learning techniques to continue transforming how users interact with and enjoy our offering of video contents and all other services.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

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:

As Executive Director, AI/ML Drug Discovery Analytics, you will be a senior leader shaping the future of data-driven drug discovery at Revolution Medicines. You will define the Research’s AI/ML strategy, oversee implementation of advanced analytics across discovery and build a world-class team to unlock the full potential of our rich internal datasets and make these insights accessible to other scientist. Your leadership will directly influence early discovery innovation, pipeline acceleration, and strategic portfolio decisions.

Responsibilities include:

Technical Leadership and Innovation: You will have a deep understanding of Machine Learning Operations and AI system design.  Design and scale a robust ML infrastructure, integrating MLOps best practices to ensure seamless development, deployment, and monitoring of AI/ML models.

Drive innovation in applying deep learning, generative models, and diffusion models to drug discovery, including target prediction, hit identification, and lead optimization. Leverage RevMed’s unique datasets to generate novel hypotheses and enable data-driven decision-making across the research continuum.

Strategic vision and Leadership: Define the long-term vision for AI/ML-enabled discovery and align it with organizational priorities.  Build, mentor, and inspire a cross-disciplinary team of data scientists, computational chemists, engineers, and biologists.  Establish key performance metrics and ensure delivery of impactful solutions that accelerate portfolio progression.

External and Cross-functional Collaboration: Forge partnerships with leading academic groups, technology innovators, and compute providers to access cutting-edge platforms and methodologies. Collaborate across research, chemistry, biology, and IT to identify high-impact opportunities for AI/ML integration and ensure smooth deployment of scalable solutions.  Act as a thought leader internally and externally, representing RevMed at scientific forums and shaping the broader field of AI-driven drug discovery.  Work closely with the Chief Digital Officer and team to build and drive the research vision for advanced analytics within the enterprise framework.  Lead the cross functional analytics team to harness data science and AI to accelerate early drug discovery.  

Required Skills, Experience and Education:

• Ph.D. or Masters degree in Computer Science, Machine Learning, Physics, Math or a relevant scientific discipline with over 10+ years’ experience, exposure to drug discovery is a plus.

• Expertise in a wide variety of AI/ML-based computational techniques and developing adaptable ML workflows to solve challenging problems.

• Deep understanding of AI/ML techniques such as deep learning, reinforment learning and generative models.

• Expertise in frameworks such as PyTorch/TensorFlow, training, and fine-tuning models on GPUs.

• Track record of deploying AI/ML solutions at scale.

• Proven track record of leadership and cross-functional collaboration across ML-Scientist, Software Engineering, and MLOps.

• Previous experience leading large AI/ML projects that require engaging with collaborators across the board and with varying degrees of expertise.

• Expertise in machine learning infrastructure and MLOps, including cloud and on-prem compute environments.

• Demonstrated ability to build, scale, and lead high-performing cross-functional teams.

• Strong communication and leadership skills with the ability to bridge diverse scientific and technical disciplines.

• 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.

• Knowledge of oncology therapeutic area and drug discovery.

• Strong familiarity with biological and chemical datasets and compound libraries.

• Evidence of successful coaching, mentorship and development of both individuals and teams in order to build long-term organizational capability.

#LI-Hybrid  #LI-GL1

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

We are hiring an Applied Scientist to help advance personalization across the Crunchyroll ecosystem. In this role, you will lead the scientific development of recommendation, ranking, and decisioning solutions that improve how fans discover and engage with anime series/movies, manga, merchandise, games, and other areas in the anime fandom. You will partner closely with Machine Learning Engineers, Product, Engineering, Marketing, and Content stakeholders to make Crunchyroll the ultimate destination for anime experience.

About the role

In the role of Senior Applied Scientist for Recommendation and Personalization, you will report to the Director of Data Science and Machine Learning in our Center for Data and Insights. You will own the research and applied science agenda for personalization, from problem framing and data exploration through model development, evaluation, experimentation, and iteration. This role is ideal for someone who enjoys combining strong scientific rigor with product thinking to improve user discovery, engagement, retention, and long-term fan value.

You will work across multiple user touchpoints, including app and web interfaces, lifecycle and promotional email campaigns, and flywheels that connect video, ecommerce, manga, and adjacent experiences. You will help define what great personalization looks like at Crunchyroll, build the evidence to prove impact, and collaborate with engineering partners to ensure the resulting solutions can be productionized effectively.

This position is based in our Los Angeles office, but we will consider our San Francisco office as a secondary location. We work a hybrid schedule, in-office three days a week: Tuesday, Wednesday, and Thursday. 

Core areas of responsibility

• Lead the research and development of recommendation, ranking, retrieval, and personalization methods tailored to Crunchyroll use cases across streaming, manga, ecommerce, and lifecycle marketing surfaces.
• Frame ambiguous business and product questions into clear scientific problems, hypotheses, success metrics, and experimentation plans.
• Design and run robust offline evaluation frameworks for recommender systems, including relevance, diversity, novelty, coverage, calibration, and long-term value metrics.
• Partner with Product, Analytics, and Engineering to define online experiments, interpret results, and turn learnings into roadmap decisions and model improvements.
• Develop user, content, and contextual understanding through feature design, representation learning, segmentation, and behavioral analysis.
• Prototype and evaluate a range of approaches, including collaborative filtering, content-based methods, sequence modeling, deep learning, bandits, causal or uplift methods, and LLM-enabled recommendation techniques where appropriate.
• Analyze user feedback loops and cross-domain interactions to improve discovery across video, merchandise, manga, and other ecosystem experiences.
• Work closely with Machine Learning Engineers to translate promising research into production-ready solutions on our in-house recommendation platform.
• Communicate scientific findings, model tradeoffs, and business implications clearly to technical and non-technical stakeholders.
• Help establish best practices for experimentation, reproducibility, model governance, and scientific documentation within the personalization and recommendations function.

About you

We get excited about candidates, like you, because you have:

Experience: You bring 5+ years of experience in applied machine learning, recommendation systems, search/ranking, experimentation, or a closely related area, with a track record of driving measurable product impact.

Scientific Depth: You have strong foundations in machine learning, statistics, experimental design, and causal thinking, and you know how to choose the right level of modeling complexity for the problem at hand.

Recommendation Expertise: You have hands-on experience with at least some of the following: collaborative filtering, retrieval and ranking systems, representation learning, sequence / generative models, bandits, graph methods, or personalization for consumer products.

Technical Skills: You are highly proficient in Python and comfortable working with common ML libraries such as PyTorch, TensorFlow, Scikit-learn, XGBoost, or similar tooling. Experience working with SQL, distributed data processing, and cloud-based ML workflows is strongly preferred.

Experimentation Mindset: You know how to design offline and online evaluations, reason carefully about metrics, and connect experimental findings to user and business outcomes.

Cross-Functional Collaboration: You have experience partnering effectively with engineers, product managers, analysts, marketers, and business stakeholders to move from idea to execution.

Communication Skills: You can explain sophisticated modeling decisions and ambiguous findings in a clear, decision-oriented way to diverse audiences.

Educational Background: You hold an MS or PhD in Computer Science, Machine Learning, Statistics, Operations Research, Economics, or a related quantitative discipline, or you bring equivalent applied industry experience.

Nice to have

• Experience personalizing content, commerce, media, entertainment, gaming, or subscription products at scale.
• Familiarity with recommender-system failure modes such as popularity bias, cold start, sparse feedback, and feedback loop effects.
• Experience with multi-objective optimization, constrained ranking, or balancing short-term engagement with long-term user value.
• Exposure to generative AI, representation learning, or LLM applications that support recommendation and personalization workflows.
• Published research, patents, or open-source contributions in recommendation systems, personalization, applied machine learning, or experimentation.

About the team

Our centralized DS/ML team serves stakeholders across Finance, Product, Engineering, Marketing, Creatives, and Content Operations with data-driven and ML/AI-powered solutions. Within that broader organization, the Personalization and Recommendation group is building the next generation capabilities to power tailored fan experiences across every major user interface and lifecycle touchpoint. Today, the team includes engineers focused on operationalizing our recommendation platform with strong engineering excellence. This Applied Scientist role complements that foundation by bringing deeper scientific ownership to modeling strategy, evaluation, and experimentation, while partnering closely with an additional MLE hire to accelerate production impact.

Why this role is exciting

• You will help define personalization strategy across multiple surfaces instead of optimizing a single narrow funnel.
• You will work on problems that span content discovery, user engagement, retention, and cross-domain ecosystem value.
• You will influence both what we build and how we measure success, with strong exposure to partners across the business.
• You will join at a formative moment, with the opportunity to shape team standards, technical direction, and long-term roadmap.

Why you will love working at Crunchyroll

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

#LifeAtCrunchyroll #LI-Hybrid

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.

Location: Mountain View, CA
Commitment: On-site
Duration: 12 weeks starting in 2026
Conversion Opportunity: High-performing interns will be evaluated for full-time offers

About the Program

We're launching our 2026 Engineering Internship Program, a fast-paced, high-impact opportunity designed for aspiring engineers who want to build real products, ship meaningful features, and accelerate their path into a full-time role. Over the course of 12 weeks, you’ll work closely with experienced engineers, gain hands-on mentorship, contribute directly to production systems, and help solve real challenges across NewsBreak's ecosystem. This is a paid, on-site internship based in our Mountain View headquarters. Top-performing interns will be considered for full-time offers at the conclusion of the program.

Highlighted Projects：

You will be matched to a team based on skills, interests, and business needs. Sample projects include:

MSP Monetization – Mountain View, CA

MSP is our next-generation, AI-powered monetization platform that empowers publishers to unlock their full revenue potential with unmatched transparency and control. It combines intelligent optimization, real-time insights, and seamless ad management to help publishers confidently scale their business and maximize long-term growth.

Newsletter Systems – Mountain View, CA

Aigeon.ai is an exciting new product built by NewsBreak, the leading platform for local news and information serving tens of millions of users across the United States. Aigeon is reimagining the newsletter and content-monetization space via AI: simplifying creation, audience growth, and monetization of newsletters for content creators and small media brands. 

NBot – Mountain View, CA

Drive the optimization of conversational experiences that power our next-generation news recommendation engine, enabling more personalized, intuitive, and intelligent user interactions.

AI Initiatives – Mountain View, CA

This initiative explores cutting-edge NLP, generative AI, and multimodal technologies to power the next generation of content intelligence. The project includes building AI-driven content generation capabilities that significantly expand the content supply while enhancing accuracy, quality, and user relevance. The goal is to create scalable AI systems that deliver meaningful impact to tens of millions of NewsBreak users.

Foundational Requirements:

• Currently in the final semester of a Master’s or PhD program in Computer Science (or a closely related field), or recently graduated from a top-tier university.
• Strong proficiency in at least one major programming language (e.g., Python, Java, C++, Go).

Preferred Qualifications:

• Coursework, academic research, or hands-on projects in Machine Learning, Artificial Intelligence, NLP, Recommendation Systems, or Large Language Models
• Experience using ML frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn)
• Familiarity with data pipelines, model training, or evaluating ML models
• Prior internships or project experience involving ML-powered features, AI agents, or AIGC systems

We’re seeking builders with diverse technical backgrounds, whether you’re a full stack engineer, machine learning engineer, or mobile engineer, who are excited to solve real problems with cutting-edge AI technologies. If you’re passionate about the latest advancements in AI, have built your own apps or projects, or naturally think with an entrepreneurial, ownership-driven mindset, you’ll thrive in this program. We value candidates who are curious, hands-on, and eager to turn ideas into impact.

Hourly Pay for internship: $40-$50