Senior-Staff Machine Learning, Responsible AI, Gen AI, Engineer

Job Description :

At Saab. Inc we are building a team of experts that will create the next state-of-the-art in AI / ML and AI / ML enabled dual use, multi-domain Autonomy solutions.

We are committed to developing AI technologies that are safe, ethical, and aligned with responsible AI principles.

Our team works on cutting-edge solutions to ensure that autonomous systems operate within the bounds of ethical guidelines and societal expectations, particularly in high-stakes environments.

We are seeking a talented and motivated Machine Learning Scientist to join our team to help us deliver this vision.

The successful candidate will leverage ML, Generative AI and Large Language Models (LLMs) to develop rigorous methods for the test and evaluation of unmanned autonomous systems for responsible behaviors in simulated environments that mimic real life scenarios.

This role is focused on ensuring that our autonomous systems achieve high quality sim2real transfer of responsible AI behaviors and align with responsible AI principles when deployed in real world scenarios.

As a Senior Machine Learning Engineer, you will also be directly contributing toward progressing Saab Inc’s forward-looking vision in AI / ML / Autonomy.

You will work on multiple applied research projects in collaboration with other Saab scientists and engineers and external university partners.

You will push the industry state of the art (SOTA) in Mchine Learning, GenAI and LLMs for creating best in class Responsible AI Autonomy solutions and standards.

Your research will result in high quality publications in leading AI / ML conferences and journals. You will be integral to all aspects of the research lifecycle including writing proposals and whitepapers, formulating problems, defining research scope, developing new solutions, conducting experiments, synthesizing results, gathering data, building prototypes, and communicating the significance of your research.

Additional responsibilities include working closely with senior leadership in writing high quality proposals in response to government agency announcements.

This position, while remote, requires travel to our university partners / collaborators as needed to support in-person milestone updates to our external customers and to maintain continuity of effort and interactions.

Occasional travel to our San Diego office is also expected. If you reside in the San Diego area the position is Hybrid (3 days / week in the office, 2 days / week remote) work.

This position is a perfect match for a visionary scientist / engineer who is passionate about the unlimited potential of ML and Generative AI and especially Responsible AI for solving real world problems and empowering society and industry.

To be successful in this role, you are a leader, a team player, and mission focused. You have a research-to-product mindset.

You will be cross-functional. You are empathetic, curious, and incredibly detail-oriented and organized. You read documentation thoroughly and are comfortable asking questions and seeking help.

You are an independent worker and critical analytical thinker.

Responsibilities :

Be the resident expert and continuously monitor the SOTA in GenAI, LLM’s, Responsible AI (RAI), and Machine Learning (ML), for enabling the development of a variety of Responsible and Intelligent Autonomous system applications.

Stay informed and be up-to-speed on all relevant trends, advancements and breakthroughs.

Develop and implement generative AI models, including GANs, VAEs, RL and LLMs, to create diverse and complex scenarios for testing autonomous agents.

Develop and Integrate LLM based agents with Autonomous Systems simulators to automate the process of evaluating and benchmarking Autonomous Systems against RAI and Ethical AI (EAI) principles.

Explore training of small, domain specific, LLM’s for a variety of internal and external use cases.

Design and execute rigorous simulation-based testing frameworks to proactively identify and assess potential risks in Saabs AI enabled Autonomous systems.

Specifically, design simulation environments that accurately replicate the operational contexts of autonomous systems, with a focus on stress testing unmanned autonomous systems (UxV’s) along vectors of increasing ethical difficulty.

Translate AI safety principles into practical, implementable measures and drive the development and rollout of cutting-edge safeguards.

Develop quantifiable metrics for the evaluation of the behaviors of autonomous systems (UxV’s) within these scenarios to ensure compliance with subjective RAI principle and EAI guidelines, and operational safety standards.

Develop quantifiable oversight and assurance metrics, aligned with RAI and Ethical AI principles, to ensure RAI properties (similar to Anthropic RSP) are upheld with the highest degree of integrity.

Collaborate with cross-functional teams, including ethicists, engineers, and domain experts, to integrate ethical considerations into the development and evaluation processes.

Stay current with the latest research and advancements in generative AI, machine learning, and autonomous systems, and apply this knowledge to enhance our evaluation frameworks.

Document methodologies, experiments, and findings in detailed technical reports and present results to stakeholders.

Create and shape an inclusive, collaborative, and inspiring working culture in working closely with teams of professors and graduate students in the co-development of solutions to satisfy all customer expectations and milestones.

Interface and collaborate with university PI’s and graduate students in managing and progressing all project milestones by continuously monitoring progress, pre-empting roadblocks and providing actionable solutions.

Lead the technology transfer of research results to Saab Inc’s internal applied engineering teams and assist in productionizing in a co-development mode.

Create and publish high quality, applied and research, publications and represent Saab in US defense forums and at top conferences such as, RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI.

Support all internal strategic planning and operations reviews including post hoc analyses and lessons learnt. Support PI’s with milestone reviews with internal and external customers.

Mentor junior engineers and assist with learning and knowledge share related to RAI and GenAI within Saab Inc.

Socialize key milestones with industry, academia, and government through conference presentations, technical paper publications, and media relations.

Compensation Range : $154,300-$204,500

The compensation range provided is a general guideline. When extending an offer, Saab, Inc. considers factors including (but not limited to) the role and associated responsibilities, location, and market and business considerations, as well as the candidate's work experience, key skills, and education / training.

Skills and Experience :

Required Skills / Experience :

Advanced degree, MS (5+yrs), PhD (2+ yrs), in Engineering, Machine Learning, Robotics, or a related analytical discipline.

Demonstrable R&D experience in ML, Gen AI, LLMs and Responsible AI fundamentals and SOTA methods.

Demonstrated experience with responsible and explainable AI principles as well as ethical considerations in AI / ML data, models, and methods.

Strong background in generative models (GANs, VAEs, etc) and large language models (e.g., GPT 4.o, etc) and the use of LLMs in creating automated evaluation tools.

Experience with one or more simulation environments and tools such as Unity, Unreal Engine, Carla, AirSim, PX4 SITL, and underlying physics engines or other custom simulation frameworks.

Proven track record of research and development in AI / ML, GenAI, RAI demonstrated through publications, patents, or significant projects.

Ability to codify abstract and subjective responsible AI principles into testable and quantifiable metrics using techniques such as fairness-aware learning, explainable AI (XAI), and adversarial testing.

Experience with developing design of experiments (DOE) using Bayesian Optimal experimentation for exploring design space.

Proficiency in programming languages such as Python, and deep-learning frameworks such as TensorFlow or PyTorch, Keras etc.

Strong analytical and problem-solving skills, with the ability to translate theoretical concepts into practical solutions and prototype implementations.

Excellent communication skills and the ability to work effectively in a collaborative team environment.

Strong interpersonal skills and an ability to build effective working relationships is a must, especially across government and industry.

Excellent oral and written communication skills with a proven ability to communicate well with peers and different levels of management and the customer.

Proven leader who motivates, inspires, and teaches others.

Strong work ethic and self-motivate and pro-active in seeking out the best solution / s.

Must exhibit leadership for executing practical application of engineering processes on a development program and maintaining engineering rigor while balancing cost, technical, and schedule.

Strong technical leadership with a research-to-product mindset, including experience leading teams of senior researchers and engineers.

Desired (good to have) Skills / Experience :

Demonstrated experience in developing and applying SOTA ML solutions to unmanned autonomous systems such as UAV’s, UxV’s, Robotic navigation.

Familiarity with perception sensing modalities, EO / IR, RADAR, LiDAR, Ultrasonics, etc.

Proficiency in RL libraries (e.g., OpenAI Gym, Stable Baselines, MuJoCo, PyBullet, etc.) and robotics platforms (e.g., ROS).

Experience with simulation environments for training and testing autonomous systems, such as Gazebo, AirSim, or PX4 SITL.

Experience with Safe-RL, Hierarchical RL, Massively Parallel RL, and Adaptive Stress testing RL.

Familiar with LLM training and issues with grounding in LLMs and other issues related to loss of realism.

Experience with exploring the space of ethical difficulty for autonomous systems through optimized DOEs through techniques such as BOE, LLM-Prompting etc.

Familiarity with RAI principles as in ELSI, ROE, IHL and with Responsible and Safe AI frameworks such as, Anthropic, FAT-ML, OECD, etc.

Experience in Modern control theory including Adaptive / Robust control, Optimal Control, MPC, Neural decision making, Barrier functions, Reachability etc.

Experience in working with multimodal perception modalities and good understanding of DL based CV architectures.

Research publications in major conferences (RSS, ICRA, CoRL, CVPR, ICLR, ICML, NeurIPS, ICCV, AAAI, etc.).

Deep mathematical / statistical understanding of learning architectures, learning theory, uncertainty quantification, explainability, etc. is a plus.

Experience with Multi-Agent Systems, Game Theory, Bayesian Networks.

Experience in Modern control theory including Adaptive / Robust control, Optimal Control, MPC, Neural decision making, Barrier functions, Reachability etc.

Experience leading fundamental and / or applied research projects focused on autonomous systems.

Experience working in the DoD contracting industry.

Status requirements

Must be a US citizen and be eligible for security clearance if needed.

Citizenship Requirements :

Must be a U.S. citizen. Applicants selected may be subject to a government security investigation and must meet eligibility requirements for access to classified information.

Drug-Free Workplaces :

Saab is a federal government contractor and adheres to policies and programs necessary for sustaining drug-free workplaces.

As a condition of employment, candidates will be required to pass a pre-employment drug screen.

Benefits :

Saab provides an excellent working environment offering professional growth opportunities, competitive wages, work-life balance, business-casual atmosphere and comprehensive benefits :

Medical, vision and dental insurance for employees and dependents

Paid time off including : minimum of 3 weeks vacation, 5 floating holidays, 8 designated holidays, parental leave, personal illness, bereavement, jury duty, long-term and short-term disability

401(k) with immediate vesting on employer match

Tuition assistance

Student loan assistance

Wellness account, Care.com subscription and employee assistance programs

Employee stock purchase program with employer match