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

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.

Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock thier abilties in orchestration with intelligent machinges.

Position Overview: 

As a Senior Autonomy Engineer on our R&D team, you'll help define the next generation of software that lets robots perceive, learn, and act in unstructured indoor environments. You'll work across the modern autonomy stack — from learned perception and prediction to mapping and motion planning — and ship capabilities that generalize across our fleet. We're looking for someone equally comfortable reading a fresh arXiv paper, writing production C++/Python, and debugging behavior on a real robot in the lab. You'll help set technical direction, raise the bar on engineering quality, and mentor others on the team.

Essential Job Functions:

• Design, train, and deploy machine learning systems for perception, SLAM, prediction, and motion planning that enable safe navigation around people and obstacles.
• Build and improve learned components — including transformer-based perception, vision-language models for scene understanding, diffusion or imitation-learning policies, and neural/Gaussian-splatting approaches to mapping — and integrate them with classical estimation and planning where it makes sense.
• Translate state-of-the-art research (papers, open-source releases, conference talks) into production-quality implementations on the robot.
• Develop data engines and evaluation infrastructure that turn fleet logs into training data, regression tests, and shipped improvements.
• Own features end-to-end: from prototype, through sim and on-robot validation, to fleet rollout, with measurement of real-world impact.
• Improve runtime performance of perception, mapping, and planning on embedded GPU/accelerator hardware (quantization, distillation, kernel work where warranted).
• Contribute to internal frameworks, simulation tooling, and developer experience that compound team velocity.
• Provide guidance and mentorship to engineers across robotics, ML, and the software systems that support them.

Education and/or Work Experience Requirements:

• Master’s Degree. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field — or equivalent demonstrated experience.
• 5+ years of relevant industry or research experience building autonomy, perception, or ML systems 
• Strong fluency in Python and C++ in a Linux environment.
• Demonstrated track record of taking research ideas and papers into deployed implementations.
• Depth in one or more of: machine learning (supervised, self-supervised, imitation, RL), SLAM and state estimation, motion planning, or 3D perception.

Required Knowledge, Skills, Abilities, and Other Characteristics:

• Hands-on experience with PyTorch (and/or JAX), modern training pipelines, and contemporary architectures (transformers, diffusion models, vision-language-action models).
• Experience designing robotic systems with ROS 2 (or comparable middleware) and contemporary simulation tools such as Isaac Sim, MuJoCo, or Gazebo.
• Comfort with the full ML lifecycle: data curation and labeling strategy, large-scale training, offline and online evaluation, and continuous deployment to production hardware.
• Solid systems and software architecture instincts; pragmatism about when a learned approach beats a classical one and vice versa.
• Familiarity with modern engineering practices: CI/CD, code review, observability, and iterative delivery (i.e. Agile, Scrum).
• Bonus: Contributions to open-source robotics or ML projects, publications at top venues (CoRL, RSS, ICRA, NeurIPS, CVPR, ICML), or experience with on-device acceleration (TensorRT, ONNX, custom CUDA kernels).

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential functions may require maintaining the physical condition necessary for sitting, walking or standing for periods of time; operating a computer and keyboard; talk and hear at normal room levels; using hands to finger, grasp, and feel; repetitive motion; close visual acuity to prepare and analyze data and figures; transcribing; viewing a computer terminal; extensive reading; lift, push, carry, or pull up to 20 pounds. 

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

Salary Range:

The anticipated salary range for candidates who will work in San Diego, California is $151,545 to $183,449. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi-state employer and this salary range may not reflect positions that work in other states.

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Brain Corp is a San Diego, California, USA-based AI company creating transformative core technology for the robotics industry. Our purpose is to create autonomous technology that helps the real world work better. Brain's robotic and AI solutions help retailers ensure that the right product is on the right shelf at the right price, in a clean environment. Through the BrainOS® Robotics Platform, which powers the largest global fleet of the Autonomous Mobile Robots (AMRs) in operation in commercial public spaces, Brain Corp delivers insightful and efficient automated solutions in both commercial floor cleaning and inventory management, empowering organizations and their employees to achieve more. Brain Corp currently powers more than 30,000 AMRs, representing the largest fleet of its kind in the world. Brain Corp is funded by the SoftBank Vision Fund, Clearbridge, and Qualcomm Ventures.

Named a top workplace by the San Diego Union Tribune and USA today in 2025, we make life-changing impacts through innovation, helping workers globally unlock thier abilties in orchestration with intelligent machinges.

Position Overview:

As a Staff Autonomy Engineer on our R&D team, you'll be one of the technical leaders setting direction for the AI that powers our robots. This is a hands-on technical leadership role: you'll architect systems that span perception, mapping, prediction, and planning; drive multi-quarter initiatives from research idea to fleet rollout; and raise the technical bar across the org. You'll work across team boundaries, partnering with engineering managers, product, and hardware to make decisions that ripple through the roadmap. You'll also be someone the team learns from — through code review, design review, mentorship, and the standards you set in your own work. We expect Staff engineers to be comfortable in deep technical waters across the modern autonomy stack: foundation models, learned policies, classical estimation and planning, and the production systems that knit them together.

Essential Job Functions:

Technical Leadership and Direction

• Set technical direction for major areas of the autonomy stack — perception, SLAM, prediction, planning, or the ML systems underneath them — and own the multi-quarter roadmaps that follow.
• Lead large, ambiguous projects end-to-end: scope the problem, pick the approach, drive execution across multiple engineers, and ship to the fleet.
• Make and defend the build-vs-borrow, learn-vs-classical, and depth-vs-breadth decisions that shape what the team works on for the next year.
• Partner with engineering managers, product, and hardware on staffing, sequencing, and risk; serve as a senior technical voice in cross-functional planning.
• Represent the team externally where useful — publications, conferences, recruiting, customer technical conversations.

Technical Excellence

• Architect and contribute to systems spanning learned perception (transformer-based detectors, VLMs for scene understanding), neural and classical SLAM (including Gaussian splatting and implicit representations where they earn their keep), behavior prediction, and motion planning.
• Drive adoption of modern learning approaches — imitation learning, diffusion policies, vision-language-action models, RL where appropriate — and integrate them with the classical components that still do real work in production.
• Build and improve the data engines and evaluation infrastructure that turn fleet logs into training data, regression suites, and shipped wins.
• Lead performance and deployment work on embedded compute: model optimization, quantization, distillation, and runtime engineering on GPU/accelerator hardware.
• Stay current with the literature and translate the parts that matter into our codebase — and recognize the larger fraction that doesn't.

Mentorship, Hiring, and Culture

• Mentor Senior and mid-level engineers; raise the bar through design review, code review, and the technical standards you model.
• Play a leading role in hiring: shape interview loops, calibrate decisions, close strong candidates, and own onboarding for new hires on the team.
• Champion engineering practices that compound — testing, observability, documentation, simulation infrastructure, developer tooling — and invest in the parts of the org that enable everyone else to ship faster.

Education and/or Work Experience Requirements:

• Master’s Degree. or Ph.D. in Computer Science, Robotics, Electrical Engineering, or a related field — or equivalent demonstrated experience.
• 7+ years of industry experience in embodied AI (robotics, self-driving, drones, or similar), with at least some of that time in a senior or lead capacity.
• Deep expertise in two or more of: machine learning, SLAM and state estimation, robotic perception, motion planning.
• Strong fluency in C++ and Python in a Linux environment.
• Demonstrated history of taking research ideas into production at meaningful scale.

Required Knowledge, Skills, Abilities, and Other Characteristics:

• Deep, hands-on expertise with PyTorch (and/or JAX), modern training infrastructure, and contemporary architectures (transformers, diffusion models, VLA/foundation models).
• Extensive experience designing robotic systems with ROS 2 (or comparable middleware) and modern simulation environments such as Isaac Sim, MuJoCo, or Gazebo.
• Strong record of shipping ML-driven features to production hardware — including the post-launch reality of monitoring, debugging weird failure modes, rollback, and on-call.
• Excellent systems and architectural judgment; able to defend a position and equally able to update it when the evidence changes.
• Modern software engineering fundamentals: CI/CD, code review culture, observability, and iterative delivery.
• Excellent written and verbal communication — design docs that set direction, talks that bring people along, and code that other engineers want to read.
• Bonus: experience with on-device acceleration (TensorRT, ONNX, custom CUDA kernels), large-scale data infra, or leading distributed teams.
• Bonus:Track record of research impact (publications at venues like CoRL, RSS, ICRA, NeurIPS, CVPR, ICML — or open-source equivalents) and of converting research into product.

Physical Demands:

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. Essential functions may require maintaining the physical condition necessary for sitting, walking or standing for periods of time; operating a computer and keyboard; talk and hear at normal room levels; using hands to finger, grasp, and feel; repetitive motion; close visual acuity to prepare and analyze data and figures; transcribing; viewing a computer terminal; extensive reading; lift, push, carry, or pull up to 20 pounds. 

Work Environment:

The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. The noise level in the work environment is usually quiet to moderate. Employees are exposed to the typical office environment with computers, printers and telephones.

Salary Range:

The anticipated salary range for candidates who will work in San Diego, California is $169,525 to $205,215. The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to the type and length of experience within the job, type and length of experience within the industry, education, etc. Brain Corp is a multi-state employer and this salary range may not reflect positions that work in other states.

In addition to base pay, our competitive total rewards package consists of:

• A discretionary annual target bonus
• Stock options
• 401(k) plan with match (no waiting period and immediate vesting)
• Comprehensive suite of insurance benefits for employees (and their families) to include a variety of medical plan options (including an HSA with employer contribution), dental, vision, life and disability insurance, Employee Assistance Program (EAP), Legal/Identity support plans, pet insurance.
• Access to Flexible Spending Accounts (Medical and Dependent Care)
• Generous paid time off including flexible vacation, Paid Sick Leave, time off for volunteering in the community, 10 paid company holidays, and a winter company shutdown

Additional Perks include:

• Daily on-site lunch available in the San Diego office
• On-campus gym including pool and tennis courts in the San Diego office
• Opportunities to connect with colleagues including monthly game nights, hikes, wellness challenges, and community events 
• Internal continuous learning events 
• Opportunities to share your own interests and hobbies with the Company

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.

#LI-HYBRID

#LI-CS1

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. 

About the Team 

The Sensors Division at STR focuses on technology development for advanced sensor systems and platforms in support of national security. The Systems Autonomy, Analysis, and Modeling (SAAM) Group within the Sensors Division develops, adapts, and applies cutting-edge autonomy research to solve real-world problems on the foundation of physics-based modeling and simulation. Algorithmic areas of interest include AI/ML, controls theory, sensor signal processing (especially radar and EO/IR), tracking, optimization, and resource allocation. Application domains include: manned air platforms (e.g., the F-35 Joint Simulation Environment), unmanned air platforms, and space assets, primarily for the Air Force and Navy as well as DARPA research programs.

The Role: 

The SAAM Group is seeking a Senior Researcher to research, design, develop, and implement a portfolio of capabilities to further our autonomy mission.  You will participate in multi-disciplinary teams spread across multiple STR campuses to plan and execute technical efforts, prepare reports & deliver talks for customers, contribute to proposal efforts, and develop innovative solutions to complex and challenging national security problems.  Specifically, you will focus on innovating and applying AI/ML and other decision-making algorithms to develop autonomy capabilities, particularly in simulation.

A successful candidate will have a demonstrated ability to successfully carry out research projects and make rapid progress with limited supervision. This position also requires skills in software development, oral communication, written communications, and peer leadership.

Interviews for this role will require an in-person or virtual presentation. 

What you will do: 

• Design, develop, and modify cutting-edge machine learning and other algorithms to conduct studies and form conclusions for autonomy and other challenges
• Create, expand, upgrade, and maintain algorithms in software
• Design, develop, validate, and manage large-scale simulations and simulation tools
• Contribute to comprehensive technical reports and presentations for government customers, articulating the implications of simulation findings on national security

Who you are:  

• This position requires the ability to obtain a Security Clearance at the Secret (S) level, for which US citizenship is needed by the U.S government
• BS +5 years’ experience, MS +3 years’ experience, or PhD in Electrical Engineering, Physics, Applied Mathematics, or related field
• Good programming skills in one or more scientific programming languages, such as C/C++, Python, or MATLAB; preferably in Linux.
• Some experience or interest in at least two of the following: machine learning, algorithm development, modeling & simulation, optimization, controls, signal processing, tracking, electronic warfare, resource allocation.
• Strong technical writing and communication skills

Even better:

• Active Secret or TS/SCI clearance
• Advanced degree in Electrical Engineering, Physics, Applied Mathematics, or related field
• Experience with mission simulators such as AFSIM or NGTS or physics-based simulators such as XPatch or Crisp
• Experience with machine learning tasks such as image recognition, deep reinforcement learning, semantic segmentation, graph neural networks, and tools such as PyTorch, Tensorboard, and Ray.
• Experience writing proposals and/or giving briefings to both highly technical and less technical audiences

Pay Information
Full-Time Salary Range: $134,000 - $174,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate’s experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.

About the Team 

The Sensors Division at STR focuses on technology development for advanced sensor systems and platforms in support of national security. The Systems Autonomy, Analysis, and Modeling (SAAM) Group within the Sensors Division develops, adapts, and applies cutting-edge autonomy research to solve real-world problems on the foundation of physics-based modeling and simulation. Algorithmic areas of interest include AI/ML, controls theory, sensor signal processing (especially radar and EO/IR), tracking, optimization, and resource allocation. Application domains include: manned air platforms (e.g., the F-35 Joint Simulation Environment), unmanned air platforms, and space assets, primarily for the Air Force and Navy as well as DARPA research programs.

The Role: 

The SAAM Group is seeking a Senior Researcher to research, design, develop, and implement a portfolio of capabilities to further our autonomy mission.  You will participate in multi-disciplinary teams spread across multiple STR campuses to plan and execute technical efforts, prepare reports & deliver talks for customers, contribute to proposal efforts, and develop innovative solutions to complex and challenging national security problems.  Specifically, you will focus on innovating and applying AI/ML and other decision-making algorithms to develop autonomy capabilities, particularly in simulation.

A successful candidate will have a demonstrated ability to successfully carry out research projects and make rapid progress with limited supervision. This position also requires skills in software development, oral communication, written communications, and peer leadership.

Interviews for this role will require an in-person or virtual presentation. 

What you will do: 

• Design, develop, and modify cutting-edge machine learning and other algorithms to conduct studies and form conclusions for autonomy and other challenges
• Create, expand, upgrade, and maintain algorithms in software
• Design, develop, validate, and manage large-scale simulations and simulation tools
• Contribute to comprehensive technical reports and presentations for government customers, articulating the implications of simulation findings on national security

Who you are:  

• This position requires the ability to obtain a Security Clearance at the Secret (S) level, for which US citizenship is needed by the U.S government
• BS +5 years’ experience, MS +3 years’ experience, or PhD in Electrical Engineering, Physics, Applied Mathematics, or related field
• Good programming skills in one or more scientific programming languages, such as C/C++, Python, or MATLAB; preferably in Linux.
• Some experience or interest in at least two of the following: machine learning, algorithm development, modeling & simulation, optimization, controls, signal processing, tracking, electronic warfare, resource allocation.
• Strong technical writing and communication skills

Even better:

• Active Secret or TS/SCI clearance
• Advanced degree in Electrical Engineering, Physics, Applied Mathematics, or related field
• Experience with mission simulators such as AFSIM or NGTS or physics-based simulators such as XPatch or Crisp
• Experience with machine learning tasks such as image recognition, deep reinforcement learning, semantic segmentation, graph neural networks, and tools such as PyTorch, Tensorboard, and Ray.
• Experience writing proposals and/or giving briefings to both highly technical and less technical audiences

Pay Information
Full-Time Salary Range: $134,000 - $174,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate’s experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing unified, multi-modal generative foundation models for multiscale biology. You will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission.

In this role, you will partner and collaborate with other multidisciplinary Scientists and Engineers across the Institute of Computation to design, build, and scale state-of-the-art foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. You will focus on the synthesis of unstructured multimodal signals with the structured relational data and knowledge graphs that represent biological reality.

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

As a Staff Machine Learning Scientist, you will use your experience to focus on designing, developing, and evaluating state-of-the-art foundation models, at scale, to benefit the research.

• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data, natural language, and structured relational inputs.   
• Architect and implement novel hybrid models that integrate Large Language Models (LLMs) with Graph Neural Networks (GNNs) for multi-hop reasoning over biological knowledge graphs .
• Develop Relational Foundation Models (RFMs) that enable zero-shot predictive tasks over heterogeneous, multi-table biological datasets.   
• Lead the design of efficient data loading strategies and distributed training recipes (e.g., FSDP, DeepSpeed) to train models across multiple GPU nodes.   
• Gain insights into model performance based on theory, deep research, and the mathematical underpinnings of set-invariant and graph-structured architectures .
• Apply strong coding experience to model development and deployment, ensuring research prototypes transition into reliable, scalable production systems.
• Stay up-to-date on the latest developments in deep learning—including native early-fusion and Mixture-of-Experts (MoE) architectures—and apply this knowledge to Altos' research .
• Mentor junior staff while maintaining a high individual technical contribution to the core research ecosystem and peer-reviewed publications.

Who You Are  

We are looking for someone who is:

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.
• Highly collaborative in mindset and ways of working across research and engineering boundaries.
• Self-motivated to drive and deliver on long-term technical projects and scientific goals.
• Demonstrates the desire to grow professionally and expand their skillset in biology, machine learning, and/or drug development.
• Able to communicate and explain the design, results, and impact of complex AI architectures to both scientific and non-scientific staff.
• Keen to contribute to seminars and scientific initiatives within Altos and the broader AI research community.

Minimum Qualifications

• PhD in Computer Science, Machine Learning, or a similar quantitative field with 5+ years of relevant work experience in academic or industry settings.
• Prior experience in developing and implementing novel generative AI models, specifically in multimodal integration, GraphRAG, or relational deep learning .
• Deep understanding of Machine Learning principles and how they apply to diverse architectures like Transformers, GNNs, and diffusion models .
• Very strong programming skills in Python and deep learning libraries (e.g., PyTorch, JAX, Hugging Face Transformers/Accelerate).   
• Proven experience with multi-GPU and distributed training at scale (e.g., DDP, FSDP, DeepSpeed, Megatron, or Ray).   
• Strong track record of published, peer-reviewed innovative AI/ML research at top-tier conferences (NeurIPS, ICML, ICLR, CVPR).

Preferred Qualifications

• Familiarity with tabular foundation models (e.g., TabPFN) and in-context learning strategies for structured data .
• Specific experience in native multimodal modeling (early-fusion) or the synthesis of LLMs and Knowledge Graphs .
• Track record of ML applied to biological data, such as NGS data (RNA-seq, ATAC-seq), biological imaging (microscopy, IF), or spatial transcriptomics.
• Experience in optimizing large-scale inference via quantization, distillation, or memory-efficient attention mechanisms.

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

#LI-NN1

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

Altos Labs is building a world-class AI ecosystem to solve the most complex problems in human biology. You will directly design and build high-performance, scalable solutions that unify high-dimensional biomedical imaging with molecular and language data.

By implementing large-scale multimodal data fusion, you will move beyond simple image analysis to create predictive models that map across biological domains. You will be hands-on with the data and the code, collaborating with our engineering team to ensure these models are scalable, efficiently trainable on distributed cloud infrastructure, and accessible to our global research community.

Responsibilities

• Model Development: Design, code, and train large-scale foundation models (e.g., Vision Transformers, Multimodal LLMs) that can embed spatial data and integrate multiple modalities.
• Hands-on Data Fusion: Implement innovative cross-domain mapping and fusion strategies to synchronize heterogeneous biological datasets.
• Scaling & Training: Build and manage high-performance ML pipelines capable of processing petabyte-scale image repositories and multi-omics streams in a cloud environment.
• Technical Collaboration: Work directly in the trenches with experimental scientists and software engineers to translate biological complexity into performant code and reliable distributed systems.

Who You Are

We are looking for a technical specialist who thrives on solving "unsolvable" problems through code and rigorous experimentation. We are open to candidates at the Scientist I, Scientist II, or Senior Scientist level based on technical expertise.

Minimum Qualifications

• Education: PhD in Computer Science, AI/ML, Biomedical Engineering, or a related quantitative field.
• Hands-on CV Expertise: Deep experience building and deploying modern Computer Vision architectures (Vision Transformers, U-Nets, Self-Supervised Learning).
• Distributed Training: Proven experience training and fine-tuning large models at scale using frameworks like PyTorch Distributed, DeepSpeed, or Jax.
• Programming Mastery: Expert-level Python skills, with a focus on building production-ready machine learning code and large-scale data management systems.
• Scientific Contributions: A track record of technical contributions via high-impact publications (CVPR, ICCV, NeurIPS, etc.) or significant contributions to open-source ML frameworks.

Preferred Qualifications

• Direct experience with Multimodal Fusion (e.g., aligning image embeddings with transcriptomic or proteomic data).
• Proficiency with cloud-native AI tools (AWS/GCP, Kubernetes, Docker) and building automated MLOps workflows.
• Experience handling the unique noise and sparsity of biological data.

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

#LI-NN1

Exact compensation may vary based on skills, experience, and location.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

What You Will Contribute To Altos

As part of our team, you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. We are open to hiring either a Machine Learning Scientist or Machine Learning Engineer.

In either role, you will be an integral part of our multidisciplinary teams building the computational platforms that will enable Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers across the Institute of Computation to contribute to the Altos research and translation ecosystem. Focussing on designing and building state-of-the-art multimodal foundation models that tackle biological questions and aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that stresses teamwork, transparency, scientific excellence, originality, and integrity. 

Responsibilities

Machine Learning Engineer

• As a Machine Learning Engineer you will focus on building, deploying and optimizing machine learning models at scale. 
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• Develop efficient data loading strategy and performance tracking to train large models with distributed training across multiple nodes 
• Ability to apply software engineering skills to develop reliable, scalable, performant distributed systems in a cloud environment.

Machine Learning Scientist

• The ideal candidate will be able to use their experience to focus on designing, developing and evaluating state of the art foundation models, at scale, to benefit the research.
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and natural language inputs.
• You will be able to gain insights, based on theory, deep research and the mathematical underpinnings of your work.
• Be experienced in using AI as a tool to accelerate your research.
• Can apply strong coding experience to model development using existing languages(s) and framework(s)

Who You Are

We are looking for someone who is :

• Excited about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities and how they can contribute
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Demonstrates the desire to grow professionally and expand their skillset and knowledge;  is keen to learn more about biology, computational science, and drug development.
• Ability to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Is able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

Machine Learning Engineer

• MS in Computer Science, Statistics, Machine Learning, Artificial Intelligence, or a related discipline
• 0-5 years of relevant work experience in either an academic or industry setting
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Ideally, experience in a distributed training framework, like DDP, FSDP, Deepspeed, Megatron, or HuggingFace Accelerate, Ray.
• Expertise in a subset of the following: transformers, natural language processing, multi-modality in language and/or in biology, diffusion models.

Machine Learning Scientist

• PhD in Computer Science / Machine Learning or similar fields 
• 0-5 years of relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Strong track record of published peer reviewed innovative AI/ML research 
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Familiarity with multimodal data integration, including early and/or late fusion strategies.
• Track record of ML applied to NGS data (e.g.RNA-seq, ATAC-seq, ChIP-seq, DNA methylation), biological imaging modalities (e.g. microscopy, H&E, IF), and/or spatial transcriptomics.

The salary range for Machine Learning Engineer position in San Diego

• Machine Learning Engineer I: $140,000 - $179,500
• Machine Learning Engineer II: $158,300 - $203,000

The salary range for Machine Learning Engineer position in Redwood City

• Machine Learning Engineer I: $152,600 - $195,600
• Machine Learning Engineer II: $174,200 - $223,300

The salary range for Machine Learning Scientist position in San Diego

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000

The salary range for Machine Learning Scientist  position in Redwood City

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000

Exact compensation may vary based on skills, experience, and location.

For UK applicants, before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasizes teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Redwood City, CA:

• Senior Scientist I, Machine Learning: $257,400 - $330,000
• Senior Scientist II, Machine Learning: $290,900 - $373,000
• Principal Scientist, Machine Learning: $330,800 - $424,100

The salary range for San Diego, CA:

• Senior Scientist I, Machine Learning: $239,500 - $307,000
• Senior Scientist II, Machine Learning: $262,100 - $336,000
• Principal Scientist, Machine Learning: $312,100 - $400,100

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

As a Senior or Principal Machine Learning Scientist, you will play a prominent role in developing generative AI/ML models for multi-modal, multiscale biology from virtual cells to agentic target assessment.  We are looking for a hands-on, creative, and collaborative individual to join our multidisciplinary team of scientists and engineers focused on transforming how we treat aging and disease. The successful candidate will thrive in a fast-paced environment that emphasises teamwork, transparency, scientific excellence, originality, rigor, and integrity.

Responsibilities

• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models, causal inference, diffusion models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Contribute to setting the long-term technical vision and research strategy for a core domain (e.g., multi-modal data fusion, perturbation modeling) within the Institute of Computation
• Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX) and  agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
• Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
• Act as a key technical mentor to Machine Learning Scientists and Engineers, raising the bar for scientific rigor and model robustness across the organization.

Who You Are

• Proven track record leveraging machine learning to solve real-world problems;
• Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning, cooperative agents
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar
• Experience with multi-GPU and distributed training at scale
• A team player who thrives in collaborative environments and is committed to enabling colleagues to reach their full potential through giving and requesting feedback focussed on professional growth
• Able to advise others across the wider function / company on cutting edge practices and approaches to enable the science / research. Desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine;
• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• 6+ years of of relevant post-PhD work experience in either an academic or industry setting
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences (e.g., NeurIPS, ICML, ICLR) or high-impact scientific journals.
• Excellent scientific communication skills: verbally and in writing; with computational and non-computational audiences, in informal 1-1 settings, team meetings, and formal seminars
• Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
• Proven experience applying sophisticated ML techniques to molecular and cell biological data sets (e.g., NGS, spatial omics, bioimaging).

Preferred Qualifications

• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Senior Scientist I, Machine Learning: £115,600 - £152,100
• Senior Scientist II, Machine Learning: £131,900 - £173,500
• Principal Scientist, Machine Learning: £173,700 - £228,600

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute to Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source software

The salary range for Cambridge, UK:

• Scientist I, Machine Learning: £74,900 - £98,500
• Scientist II, Machine Learning: £107,900 - £142,000
• Senior Scientist I, Machine Learning: £115,600 - £152,100

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

#LI-NN1

What You Will Contribute To Altos

This is an opportunity to join the state-of-the-art Virtual Cell team that recently won the Generalist prize in the ARC Virtual Cell Challenge. Here you will help to accelerate and optimize our progress in developing multi-modal generative foundation models for multiscale biology. 

In this role, you will be an integral part of our multidisciplinary teams enabling Altos to achieve its mission. You will partner and collaborate with other Machine Learning Scientists and Engineers, as well as other computational scientists and biologists, across the Institute of Computation to contribute to the Altos research and translation ecosystem. This role is focused on improving our state-of-the-art “virtual cell” models, encompassing gene and protein modeling, imaging, and other modalities to aid in the discovery of novel interventions for aging and disease. 

The successful candidate will thrive in a fast-paced environment that emphasises/emphasizes *please spell differently for UK/US teamwork, transparency, scientific excellence, originality, and integrity.

Responsibilities

• Use your experience to focus on designing, developing and evaluating state of the art foundation and focused models, at scale, to advance the Altos mission
• Pre-train and fine-tune large-scale machine learning systems using multimodal biological data and prior knowledge inputs.
• Pioneer novel machine learning methodologies and statistical frameworks (e.g., generative models,  diffusion/flow matching models, and advanced transformer architectures) to address fundamental challenges in cell health and rejuvenation
• Design, implement, and optimize large-scale machine learning systems using modern frameworks (e.g., PyTorch, JAX), AI-assisted coding, and agile practices
• Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters to handle terabytes of multi-modal biological data
• Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
• Participate in the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation

Who You Are

• Inspired by the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities
• Highly collaborative in mindset and ways of working
• Self-motivated to drive and deliver on projects and goals
• Focused on professional growth and expanding you skillset and knowledge
• Able to communicate and explain the design, results, conclusions and the impact of their work to both scientific and nonscientific staff.
• Able to stay up-to-date on the latest developments in deep learning and apply knowledge to their work.
• Keen to take the opportunity to contribute to seminars and other scientific initiatives within Altos and the broader scientific community.

Minimum Qualifications

• Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field, demonstrating a deep theoretical foundation in ML/AI.
• Relevant work experience in either an academic or industry setting.
• Prior experience in developing and implementing novel generative AI models in a subset of the following: transformers, multi-modality, diffusion/flow matching models.
• Can demonstrate a deep understanding and expertise of Machine Learning Principles and how they apply to different models  
• Proven experience developing and applying complex machine learning models, preferably with a significant portion of that time spent in a fast-paced industry or translational research environment.
• Very strong programming skills, including experience with Python and deep learning libraries (PyTorch, Hugging Face Transformers, H-F Datasets, H-F Accelerate)
• Experience writing production-quality code with modern machine learning frameworks such as PyTorch, TensorFlow, JAX, or similar;
• Experience with multi-GPU and distributed training at scale;

Preferred Qualifications

• Strong track record of published peer reviewed innovative AI/ML research 
• Experience in cell health and rejuvenation related research area
• Experience in the application of machine learning methods to biological data
• Experience in computational approaches to drug discovery
• Experience with software development methodologies and open-source softwar

The salary range for Redwood City, CA:

• Scientist I, Machine Learning: $200,900 - $257,500
• Scientist II, Machine Learning: $226,200 - $290,000
• Senior Scientist I, Machine Learning: $257,400 - $330,000

The salary range for San Diego, CA:

• Scientist I, Machine Learning: $179,400 - $230,000
• Scientist II, Machine Learning: $212,900 - $273,000
• Senior Scientist I, Machine Learning: $239,500 - $307,000

Exact compensation may vary based on skills, experience, and location.

Before submitting your application:

- Please click here to read the Altos Labs EU and UK Applicant Privacy Notice (bit.ly/eu_uk_privacy_notice)
- This Privacy Notice is not a contract, express or implied and it does not set terms or conditions of employment.

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