Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

• Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, safety monitoring, etc., to be run on self-driving vehicles.
• Design test harnesses for embedded software components and full systems
• Provide technical mentorship to engineers.
• Proactively work with cross-functional engineering teams to solve complex and interesting problems.
  
  

What We're Looking For:

• Experience with creating detailed requirements from use cases.
• Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
• Experience writing software for embedded platforms in C and C++.
• Experience with Test-Driven Development (TDD).
• Experience working on embedded Linux / RTOSs.
• Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
• Experience with debugging on embedded platforms.
• Experience writing software in Python and experience doing automation with shell scripting.
• Experience working with ARM Cortex MCUs or Microprocessors.
  
  

Bonus Points (not required):

• Experience working with large data pipelines, and platforms that require deterministic execution.
• Experience using inter-system communication protocols such as I2C and SPI
• Experience deploying Machine Learning models.
• Experience working with GPUs.
• Experience working directly with the Linux kernel or Device Drivers.
• Experience with Simulation and Code Generation, and knowing when their use is appropriate.
• Experience working with Bazel.
• Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

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.

Location: 439th CES/CER, 250 Patriot Avenue, Westover ARB, MA 01022 (Onsite)

Citizenship: US Citizen (MUST)

Security Clearance: Requires successful completion of NACI/SF85 (Public Trust) background investigation.

Position Overview:

The Support Specialist provides on-site, junior-level technical support to the 439th Civil Engineer Squadron (CES) at Westover ARB to help operate and sustain AI-enabled solutions in a secure DoD environment. Working under guidance from senior engineers and government stakeholders, the role supports day-to-day platform operations, basic data/model updates using established procedures, user support, and documentation for AI/ML-enabled capabilities (e.g., contract analysis, energy management, and snowfall recovery).

This position contributes to mission readiness by helping operationalize and improve critical AI-driven platforms for military engineering, utilities, contracting, and emergency response.

Key Responsibilities:

• AI/ML support: Run established training/evaluation scripts and assist with basic model validation, tuning experiments, and periodic updates under supervision.
• Deployment & integration support: Assist with deployments in secure, on-site/air-gapped environments by following checklists and runbooks; support integration testing and coordinate tickets with DoD IT/cyber teams.
• Documentation: Update and maintain technical notes, user guides, and training materials using provided templates and standards.
• Training support: Assist with recurring user training and help translate technical workflows for non-technical users; capture feedback and improvement requests.
• Security: Follow DoD cybersecurity requirements; protect CUI/FCI; comply with privacy and confidentiality rules.
• Sustainment: Perform basic monitoring and health checks; execute approved patches/updates using runbooks; troubleshoot common issues and escalate complex problems.
• Reporting: Support labor-hour reporting and contract deliverables on Government timelines.
• Coordination: Log, track, and triage support tickets/incidents; communicate status updates; coordinate with the Resources Flight Chief and technical leads to resolve issues.

Required Qualifications:

• Education: Bachelor’s degree in computer science, engineering, data science, or related field.
• Experience: Minimum of 2 years’ direct hands-on experience or commensurate education in artificial intelligence, machine learning, data science, or a related field within secure DoD or comparable environments.
• Technical Skills: Working knowledge of Python; basic Linux command line; Git/version control; ability to run and troubleshoot scripts; familiarity with at least one ML library (e.g., scikit-learn or PyTorch/TensorFlow) and basic data handling (CSV/SQL fundamentals).
• Security & compliance: Ability to follow secure handling procedures for CUI/FCI and comply with DoD/site security requirements; willingness to complete required security and privacy training.
• Communication: Clear verbal and written communication for technical and non-technical audiences; able to draft documentation and provide status updates with guidance.
• Professionalism: Present a professional appearance; display contractor identification badges at all times; adhere to all base regulations and government conduct policies.

Additional Requirements:

• U.S. citizenship; eligible for base access.
• Occasional travel to other AFRC locations, as authorized.
• Compliance with privacy, safety, and physical/environmental security rules.
• Maintain service continuity and follow contract staffing constraints.
• Maintain personally issued computing equipment per contract terms.

Preferred Qualifications:

• Prior support for .mil/.gov AI, data, or software solutions (internships/projects count).
• Familiarity with DoD acquisition/contracting and compliance processes.
• Familiarity with containers (Docker) and/or basic CI/CD concepts; interest in automation/scripting to improve repeatable support tasks.

Job Title: Senior Software Engineer
Locations: Houston, TX; Boston, MA  
Reports to: Manager, Software Engineering 

 A quick snapshot… 

As a Senior Software Engineer, you’ll be a key member in a team responsible for the development of scalable, reliable, and innovative AI/GenAI solutions. You’ll contribute to high-priority projects, ensuring maintainable code and producing high-quality, production-ready applications. You’ll operate with a high degree of technical expertise, strategic thinking, effective collaboration across diverse teams, while helping to mentor and elevate others to meet a very high technical bar.    

Why it’s a big deal…   

You will be a key contributor to delivering Conga’s AI roadmap, ensuring solutions meet high quality standards and timelines. You’ll be a core member of the team that will implement complex, large-scale AI systems. You’ll also have the opportunity to work cross-functionally to resolve issues, mentor junior members, and help to foster a culture of continuous learning and technical excellence. All of this adds up to an exciting, challenging, and always interesting place to work, where complex problems are found and solved every day. 

Here's what we’re looking for… 

Related Experience. You have 7+ years of professional software development experience, including 3+ years in AI/ML or GenAI. You have a proven track record of developing and deploying scalable, production-grade AI solutions.  

Technical expertise. You have:   

• Experience in Python and frameworks such as TensorFlow, PyTorch, FastAPI, LangChain, LangGraph, and KubeFlow.   
• Knowledge of AI/ML algorithms, generative models, and LLMs.  
• Proficiency with cloud platforms (e.g., GCP, AWS, Azure) and modern DevOps practices.  
• Strong understanding of distributed systems, microservices architecture, and database systems (SQL/NoSQL).  

  Education. A bachelor’s degree in engineering or equivalent. 

 Here’s what will give you an edge… 

Effective communication and interpersonal skills. You’re comfortable initiating and engaging in collaborative discussions. You are skilled at reading and adapting to different communication styles. When you speak, you are clear and concise. Your strong listening skills help to build trust and foster connections with our clients. They also ensure you collect the right information so you can resolve issues most expediently. 

Initiative. You do not wait around for things to happen or for someone to tell you what to do. You are not only proactive about completing your own work, but when you sense the need to introduce a project that will benefit the team or the organization -- even if it’s outside your scope of work -- you put a proposal together, talk to the team about it, and own it. And that also goes back to having an entrepreneurial spirit. 

Passionate Problem Solver. Proactive, self-driven, and enjoys solving complex problems, not just in the primary area of responsibility but across boundaries. Identify and implement best practices for coding as well as development processes and perform as a trusted contributor requiring little to no supervision and demonstrating the ability to meet deadlines, exceed goals, and create benchmarks for success. 

#LI-BR1

Role: Senior Software Engineer 
Reports to: Sr. Manager, Software Engineering 
Location: Houston, TX; Boston, MA; 

A quick snapshot…
As a Senior Software Engineer at Conga, you will be a key contributor to the design, development, and deployment of advanced AI and generative AI-based products. You will drive technical innovation, lead complex projects, and collaborate closely with cross-functional teams to deliver high-quality, scalable, and maintainable solutions. This role requires a strong background in software development, AI/ML techniques, and DevOps practices, along with the ability to mentor junior engineers and contribute to strategic technical decisions.

Why it’s a big deal…
As a Senior Software Engineer, you will play a critical role in shaping the future of Conga’s AI-powered product portfolio. You’ll lead the development of scalable, production-grade solutions that bring generative AI capabilities to life, while influencing architecture, engineering best practices, and delivery execution. Your work will directly impact product innovation, platform reliability, and the ability of our teams to build intelligent, high-performing solutions at scale.

Are you the person we’re looking for?   

Related experience.

At least 6 years of professional software development experience, including significant experience building AI/ML or generative AI applications. Demonstrated success developing scalable, production-grade software solutions and leading complex technical initiatives from design through deployment.

Technical Expertise:

• Advanced proficiency in Python, FastAPI, PyTest, Celery, and other Python frameworks
• Deep understanding of software design patterns, object-oriented programming, and concurrency
• Strong experience with cloud technologies such as GCP, AWS, or Azure
• Experience with containerization and orchestration tools such as Docker and Kubernetes
• Familiarity with CI/CD practices, version control systems such as GitHub, and work tracking tools such as JIRA
• Knowledge of generative AI frameworks such as LangChain and LangGraph, along with MLOps and AI lifecycle management
• Experience deploying and monitoring AI models in cloud environments
• Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master’s degree preferred

Education: A bachelor’s degree in Computer Science, Engineering or equivalent 

Here’s what will give you an edge… 

• Hands-on experience with advanced machine learning algorithms, including generative models, NLP, and transformers
• Knowledge of industry-standard AI frameworks such as TensorFlow and PyTorch
• Experience with data preprocessing, model evaluation, and AI model optimization
• Proficiency with relational and NoSQL databases such as MongoDB, MSSQL, and PostgreSQL
• Experience with analytics platforms such as BigQuery, Snowflake, or Tableau
• Familiarity with messaging systems such as Kafka
• Experience with test automation tools and CI/CD tooling, including Terraform and GitHub Actions
• Advanced knowledge of GCP technologies such as Vertex AI, BigQuery, GKE, GCS, and Dataflow, particularly for deploying AI models at scale 

Responsibilities:

• Design, develop, and optimize high-quality code for complex software applications and systems, maintaining high standards of performance, scalability, and maintainability
• Lead end-to-end development of generative AI solutions, from data collection and model training to deployment and optimization
• Experiment with cutting-edge generative AI techniques to enhance product capabilities and performance
• Take ownership of architecture and technical decisions for AI/ML projects
• Mentor junior engineers, review code for adherence to best practices, and promote technical excellence across the team
• Lead execution and delivery of features, managing project scope, timelines, and priorities in collaboration with product managers
• Proactively identify and mitigate risks to support successful, on-time delivery
• Contribute to architectural design and planning for new features, ensuring solutions are scalable, reliable, and maintainable
• Conduct rigorous code reviews and provide actionable feedback that supports team growth and software quality
• Design and implement robust test suites to ensure code quality and system reliability
• Advocate for test automation and CI/CD pipelines to streamline testing and maintain service health
• Monitor and maintain the health of deployed services using telemetry and performance indicators
• Perform root cause analysis for incidents and drive preventive measures to improve system reliability
• Operate in a DevOps model, taking end-to-end ownership of features and services in production
• Create and maintain thorough documentation for code, processes, and technical decisions
• Contribute to knowledge sharing and continuous improvement across the engineering organization

#LI-BR1

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

As a Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

On our Behaviors team (Prediction and ML Planner), you will have the opportunity to work with world-class ML engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The Behaviors team develops ML models that learn how different agents navigate complex real-world traffic scenarios. We leverage these models to set the behavior of our self-driving vehicle, and predict the behavior of other agents such as vehicles and vulnerable road users. 

We are looking for proven leaders and technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:

• Define and execute motion planning and prediction projects that improve our self-driving vehicles’ capability to safely, comfortably and legally navigate complex traffic scenarios
• Lead, manage and grow a team of engineers
• Design and lead the implementation of behavior models that leverage the latest advancements in machine learning, generative AI and reinforcement learning
• Productionize and deploy solutions onto autonomous vehicle fleets
• Collaborate with perception, simulation, data platform and integration teams to validate and enhance your products’ on-road performance
• Communicate strategies, progress and challenges to executive leadership

What We’re Looking for:

• Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
• Proven leadership skills at executing large, complex technical initiatives
• Extensive experience managing and leading engineers
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries
• Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods 
• Excellent communication and interpersonal skills

Bonus Points:

• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
• Experience with state of the art generative AI, and/or reinforcement learning, paradigms
• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• Strong programming skills in C++ and/or CUDA programming

On our Behaviors team (Prediction and ML Planner), you will have the opportunity to work with world-class ML engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The Behaviors team develops ML models that learn how different agents navigate complex real-world traffic scenarios. We leverage these models to set the behavior of our self-driving vehicle, and predict the behavior of other agents such as vehicles and vulnerable road users. 

We are looking for proven leaders and technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:

• Define and execute motion planning and prediction projects that improve our self-driving vehicles’ capability to safely, comfortably and legally navigate complex traffic scenarios
• Lead, manage and grow a team of engineers
• Design and lead the implementation of behavior models that leverage the latest advancements in machine learning, generative AI and reinforcement learning
• Productionize and deploy solutions onto autonomous vehicle fleets
• Collaborate with perception, simulation, data platform and integration teams to validate and enhance your products’ on-road performance
• Communicate strategies, progress and challenges to executive leadership

What We’re Looking for:

• Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
• Proven leadership skills at executing large, complex technical initiatives
• Extensive experience managing and leading engineers
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries
• Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods 
• Excellent communication and interpersonal skills

Bonus Points:

• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
• Experience with state of the art generative AI, and/or reinforcement learning, paradigms
• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• Strong programming skills in C++ and/or CUDA programming

Motional’s global headquarters are located at 100 Northern Avenue in Boston, MA. Nestled in the bustling Seaport district with sweeping views of Boston Harbor and downtown Boston, the office is located close to major transit lines and a quick walk to various restaurants and popular attractions.

Mission Summary:

Motional’s CORE team is responsible for our vehicle’s Compute and Onboard Runtime Environment. We are creating a world leading AI compute platform for autonomous vehicles. This is the system that executes the software and neural networks that make our vehicles autonomous. 

The Next-Gen Technologies team is part of CORE. We work at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s on-board vehicle architecture. If you are a software engineer and love the idea of working on embedded AI hardware and software systems to create the next generation of autonomous vehicles, we would love to talk with you. 

What You’ll Be Doing:

As a senior engineer in the Next-Gen Technologies team, you will help us improve the compute performance of our current generation and next-generation autonomous driving systems through participating in full lifecycle development from idea to proofs-of-concept to production. 

Specifically, you will:

• Focus deeply on ML model deployment, integration of multiple ML models, and ML model optimization on embedded compute platforms.
• Dive deep into the full ML software stack. Analyze ML workload performance on a variety of hardware processors, optimize ML models, improve ML software, and help us continually improve our stack through the application of efficient and effective ML approaches. 
• Design, develop, test, integrate, and optimize software and tools on a variety of ML compute architectures.
• Collaborate with deep learning experts in perception, prediction, and other autonomous driving application areas to enable algorithms on GPU, NPU, and other ML accelerator architectures.
• Optimize the utilization of GPU/NPU resources and sharing of GPU/NPU access across multiple programs running on the same system.
• Lead designs to determine the needs of the system and how to best meet those needs through continually improving our ML software stack.
• Advise peers and management on technical matters.

What We’re Looking For:

• Experience with machine learning accelerators, including GPUs, NPUs, TPUs, and their programming environments, including CUDA, TensorRT, or similar technologies.
• Strong experience with modern C++ development in a Linux environment.
• Experience with parallel and high-performance computing.
• Comfortable with experimentation and evaluating different options as we work towards finding solutions that work. 
• A degree in Software Engineering, Computer Science, Electrical or Electronic Engineering, or similar technical field of study, or you have equivalent knowledge gained through your practical experience.

Preferred, but not required:

• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
• Experience with embedded systems development for ARM-based system-on-chip architectures.
• Experience working in a MLOps or DevOps environment.
• Passion for self-driving technology and its potential for positive impact on the world.
  
  

This role is hybrid from our Boston office. It requires two in-office days each week, ideally Tuesday and Thursday.

Your Impact

We are seeking multiple highly skilled Full-Stack members of Technical Staff (MTS) to join our CoreAI organization, driving end-to-end development of AI systems across Cloud, Edge Devices, Mission Critical and Robotics platforms.

This role goes beyond pure research. You will operate across the full stack, from data, models, and infrastructure to system integration and production deployment, to deliver scalable, real-world AI solutions. You will work on cutting-edge applications spanning computer vision, NLU, multimodal AI (MLLMs), and GenAI, enabling intelligent perception, reasoning, and action in mission-critical environments.

As a senior technical leader, you will partner closely with research scientists, machine learning engineers, hardware, firmware, and product teams to translate advanced algorithms into robust, production-ready systems that operate reliably at scale.

Why This Role

You will have the opportunity to own and shape end-to-end AI systems that operate in real-world environments, bridging the gap between cutting-edge research and impactful production deployment. This role is ideal for engineers who thrive at the intersection of AI, systems, and product, and want to build scalable, high-impact solutions across cloud and edge.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own end-to-end system development across data pipelines, model development, evaluation, and deployment for AI-powered products.
• Design and build scalable, production-grade systems for real-time perception, multimodal understanding, and decision-making.
• Develop and deploy models across cloud and edge environments, including resource-constrained devices.
• Architect and optimize full-stack AI pipelines, including:
• Translate research advances in computer vision, NLU, GenAI, and multimodal LLMs into production systems.
• Collaborate cross-functionally with MLE, hardware, firmware, and product teams to integrate AI into real-world systems.
• Optimize solutions for hardware-specific acceleration (GPU, NPU, DSP) and edge deployment.
• Define and drive evaluation frameworks and metrics to ensure system performance, reliability, and safety.
• Lead technical direction for complex, ambiguous problems and influence system architecture across teams.
• Contribute to technical design docs, internal knowledge sharing, and long-term platform strategy.

Basic Qualifications

• Master’s, or PhD in Computer Science, Electrical Engineering, or related field
• 8+ years (L8) or 10+ years (L9) of industry experience building production systems
• Strong programming skills in Python/C++ and experience with modern ML frameworks (e.g., PyTorch, TensorFlow)
• Proven experience delivering end-to-end systems from concept to production
• Deep expertise in one or more areas:
• Experience building and scaling distributed systems or cloud-based ML pipelines
• Experience optimizing models for latency, cost, and deployment constraints

Preferred Qualifications

• Experience deploying AI both on Cloud (AWS, AzureML), edge devices (e.g., mobile, embedded systems, robotics platforms on Qualcomm, NVIDIA, Intel)
• Familiarity with hardware acceleration frameworks (TensorRT, ONNX, SNPE, etc.)
• Experience with real-time systems and streaming data pipelines
• Knowledge of multimodal data processing (vision, audio, text, sensor fusion)
• Experience with AWS or other cloud platforms for large-scale inference and training
• Strong system design and architecture skills across cloud ↔ edge environments
• Track record of technical leadership, mentoring, and driving cross-team initiatives
• Experience in privacy-preserving AI, security, or safety-critical systems

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Boston, MA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

Your Impact

We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own one or more key technical areas across LLM, MLLM, CV product portfolio.
• Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
• Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
• Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
• Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
• Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
• Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
• Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
• Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
• Experience coach and mentor junior scientists.

What You Bring

• PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
• Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
• Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
• Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
• Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
• Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
• Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Boston, MA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

ROLE SUMMARY 

As an Engineer on the Generative & Agentic AI team, you will play a hands-on role in building, deploying, and operating AI capabilities that power Babel Street’s intelligence applications. You will work closely with senior AI leaders, product teams, and engineers to implement generative and agentic AI solutions that support investigative, analytical, and operational workflows across the platform. 

This is an execution-focused role for an engineer with strong foundations in machine learning and generative AI who is excited to work on real-world, mission-driven applications. You will contribute directly to LLM and SLM pipelines, retrieval and grounding systems, agent workflows, and AI-enabled features—while learning how to deliver AI that is safe, reliable, cost-efficient, and production-ready. 

This is a hybrid role to be based out of either our Reston, VA/Washington DC office or our Somerville MA office.

ROLE FOCUS 

This role spans three practical execution areas: 

Generative AI & Model Development 

You will help implement and operate LLM- and SLM-based systems, contributing to prompt development, fine-tuning, evaluation, and inference optimization. You will support retrieval-augmented generation (RAG) pipelines, embeddings, and grounding techniques to ensure AI outputs are accurate, explainable, and aligned with intelligence use cases. 

Agentic AI & Workflow Automation 

You will assist in building and integrating agent-based workflows that automate analytical tasks, connect platform services, and support intelligence applications. This includes implementing agent logic, tool-use patterns, and basic orchestration under the guidance of senior engineers. 

AI Engineering & Production Delivery 

You will help productionize AI capabilities using modern AI SDLC tools and practices, contributing to evaluation, testing, telemetry, and guardrails that reduce hallucinations and ensure safe behavior. You will work within established governance frameworks to ensure AI features are measurable, reliable, and cost-aware. 

KEY RESPONSIBILITIES 

• Implement and maintain LLM and SLM pipelines, including prompt engineering, inference, and evaluation. 

• Support RAG pipelines, embeddings, and retrieval systems used in intelligence applications. 

• Assist in building agent workflows that automate analytical or operational tasks. 

• Write clean, maintainable code (Python or others) to support AI services and integrations. 

• Contribute to AI evaluation, testing, and hallucination-mitigation techniques. 

• Use AI-assisted development tools (e.g., Copilot, Cursor) to improve development velocity and quality. 

• Collaborate with Product and Engineering teams to integrate AI capabilities into user-facing workflows. 

• Follow established AI governance, safety, and cost-optimization practices. 

QUALIFICATIONS 

Required 

• 5+ years of experience in software engineering, machine learning, or applied AI roles. 

• Hands-on experience working with LLMs and/or SLMs, including prompting, inference, or fine-tuning. 

• Experience building or contributing to RAG pipelines, embeddings, or retrieval systems. 

• Familiarity with agent-based systems or workflow automation (academic, professional, or open-source). 

• Strong programming skills in Python; experience with common libraries (PyTorch, TensorFlow, etc.). 

• Solid foundation in machine learning concepts (training, evaluation, overfitting, metrics). 

• Experience using or contributing to modern AI/ML tooling and workflows (ML pipelines, evaluation scripts, model serving). 

• Ability to work in a collaborative, fast-moving, mission-driven environment. 

Preferred 

• Experience applying AI to intelligence, investigative, analytical, or risk-related applications. 

• Familiarity with vector databases, graph databases, or knowledge graphs. 

EDUCATION 

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field required. 
Advanced degree is a plus but not required. 

Benefits at Babel Street (just to name a few...)

• Health Benefits: Babel Street covers 85-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances – for you and your family!
• Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match.
• Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives.
• Holidays: Babel Street provides employees with 12 paid Federal Holidays
• Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education.                 

Babel Street is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Further, Babel Street will not discriminate against applicants for inquiring about, discussing or disclosing their pay or, in certain circumstances, the pay of their co‐worker, Pay Transparency Nondiscrimination. In addition, Babel Street's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request, we will provide you with more information about such accommodations.

ROLE SUMMARY:

As an Engineer on the Image & Computer Vision AI team, you will play a hands-on role in developing and deploying computer vision capabilities that support Babel Street’s intelligence applications. You will build systems that extract, analyze, and reason over visual data—enabling facial matching, object and scene understanding, geolocation and location inference from imagery, and multimodal intelligence workflows. 

This role is execution-focused and suited for engineers with strong foundations in computer vision, image processing, and machine learning who want to apply their skills to real-world, mission-driven problems. You will work closely with AI, Product, and Engineering teams to deliver reliable, scalable, and cost-efficient vision capabilities, including integration with multimodal LLM systems that allow users to search and reason over images using natural language. 

This is a hybrid role to be based out of either our Reston, VA/Washington DC office or our Somerville MA office.

ROLE FOCUS;

This role spans three practical execution areas: 

Computer Vision & Image Analytics 

You will implement and operate image analytics pipelines that support facial matching, object detection, scene understanding, and image similarity. This includes image preprocessing, feature extraction, model inference, evaluation, and performance optimization to meet mission-grade accuracy and latency requirements. 

Geospatial & Location Inference from Imagery 

You will contribute to capabilities that infer location, context, or environmental attributes from imagery—leveraging visual cues, metadata, and learned representations. This includes supporting image-based geolocation, landmark recognition, and contextual scene analysis used in intelligence workflows. 

Multi-Modal AI & Image Search 

You will support multimodal AI systems that combine vision models with LLMs, embeddings, and retrieval pipelines to enable natural-language search and reasoning over images and image collections. You will help integrate visual understanding into broader intelligence applications and workflows. 

KEY RESPONSIBILITIES:

• Build and maintain computer vision pipelines for image ingestion, preprocessing, inference, and evaluation. 

• Implement facial matching, and identity-related vision workflows in accordance with accuracy, safety, and compliance requirements. 

• Develop and support object detection, image similarity, and scene understanding models. 

• Contribute to image-based geolocation and location inference capabilities using visual features and contextual signals. 

• Support multimodal AI workflows that combine image embeddings with LLM-based search and reasoning. 

• Write clean, maintainable Python code and contribute to production services and APIs. 

• Assist with model evaluation, bias testing, and accuracy monitoring for vision systems. 

• Optimize inference pipelines for performance, scalability, and cost efficiency (GPU usage, batching, model selection). 

• Collaborate with Product and Engineering teams to integrate vision capabilities into user-facing intelligence applications. 

QUALIFICATIONS: 

Required 

• 3+ years of experience in computer vision, image processing, or applied machine learning. 

• Hands-on experience with computer vision models and techniques (e.g., CNNs, transformers for vision, feature embeddings). 

• Experience building or integrating image analytics such as facial recognition, object detection, or image similarity. 

• Strong programming skills in Python; experience with common CV/ML libraries (PyTorch, TensorFlow, OpenCV, etc.). 

• Solid understanding of machine learning fundamentals, model evaluation, and performance tradeoffs. 

• Experience working with large image datasets and production ML pipelines. 

• Ability to work collaboratively in a fast-moving, mission-driven engineering environment. 

Preferred 

• Experience with facial matching or biometric systems in regulated or high-stakes environments.
• Experience with image-based geolocation or scene/location inference.
• Familiarity with multimodal AI systems, including combining vision models with LLMs or natural-language search. 

EDUCATION:

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field required. 
Advanced degree is a plus but not required. 

Benefits at Babel Street (just to name a few...)

• Health Benefits: Babel Street covers 85-100% monthly premium costs for Medical, Dental, Vision, Life & Disability insurances – for you and your family!
• Retirement Plans: Babel Street offers both a Traditional and Roth 401(K) with a very competitive match.
• Unlimited Flexible Leave: We trust our employees to manage their own time and balance their personal and work lives.
• Holidays: Babel Street provides employees with 12 paid Federal Holidays
• Tuition Reimbursement: We are committed to investing in our employees. One way we do that is with our Tuition Reimbursement Program for continuing education.                 

Babel Street is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Further, Babel Street will not discriminate against applicants for inquiring about, discussing or disclosing their pay or, in certain circumstances, the pay of their co‐worker, Pay Transparency Nondiscrimination. In addition, Babel Street's policy is to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works. Upon request, we will provide you with more information about such accommodations.