At scale, quantum computers will be integrated into classical datacenters — combining the unique strengths of CPUs, GPUs, and QPUs will help us solve the world’s hardest problems. Today, we already use IonQ quantum computers in tandem with high-performance computer (HPC) clusters in applications like quantum machine learning and image analysis. As a Senior Staff Software Engineer leading our HPC integration, you’ll help build and maintain our interfaces with SLURM and other open HPC stacks.

Responsibilities:

• Lead the design and development of our HPC software stack integrations
• Establish best practices for code development, quality assurance, documentation, and continuous integration and deployment
• Lead and participate in code reviews
• Effectively self-manage projects, priorities, deadlines, and deliverables; Identify, track and mitigate execution roadblocks and technical risks
• Mentor junior staff members; we’ll ultimately be building a team around you!
• Help minimize overhead between classical and quantum resources through efficient scheduling and parallelization

You’d be a good fit with:

• Bachelor’s degree in Computer Science, IT or equivalent practical experience -- untraditional backgrounds are welcome and encouraged!
• 13+ years experience in software engineering
• 5+ years experience of open source contributions
• 2+ years experience with Slurm or other HPC batch schedulers (LSF, PBS, GridEngine, etc.) and/or other HPC technologies
• Familiarity with containerization technologies such as Docker and container orchestration platforms like Kubernetes or Microk8s
• Familiarity with MPI or other multiprocessing schemes
• Experience with workflow orchestration tools (Argo Workflows, Kubeflow)
• Significant experience with system languages like C/C++ or Go, and advanced scripting in Python
• Established experience in Linux operating system, environment, and tools

You’d be a great fit with:

• 15+ years experience in software engineering
• 10+ years experience of making open source contributions  
• 5+ years in High Performance Compute cluster management
• 2+ years experience as an open source project maintainer with an active community
• Expert-level knowledge of Fortran and/or C
• Familiarity with quantum software stacks like MQSS or OpenQSE
• Familiarity with distributed computing frameworks like Ray or Dask
• Experience with GPU programming models such as CUDA (or even better: CUDA Quantum)
• Expert analysis skills in areas like statistical testing, modeling and general optimization
• Knowledge of one or more domains of computational physics (PDEs, n-body, large-dimension integration, stochastic systems, ...)
• Familiarity with common machine learning frameworks like PyTorch or TensorFlow
• Exposure to quantum physics and/or quantum information science

Location: This is a hybrid role based at our headquarters in College Park, MD or at our Bothell, Washington facility.
Travel: 10%
Job ID: 1135

The approximate base salary range for this position is $187,358- $245,300. The total compensation package includes base, bonus, and equity.

Senior Machine Learning Engineer - Model Evaluations, Public Sector

The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, agentic models, and multimodal pipelines—into mission-critical government environments. We build evaluation frameworks that ensure these models operate reliably, safely, and effectively under real-world constraints. As an ML Engineer, you will design, implement, and scale automated evaluation pipelines that help customers trust and operationalize advanced AI systems across defense, intelligence, and federal missions.

You will:

• Develop and maintain automated evaluation pipelines for ML models across functional, performance, robustness, and safety metrics, including LLM-judge–based evaluations.
• Design test datasets and benchmarks to measure generalization, bias, explainability, and failure modes.
• Build evaluation frameworks for LLM agents, including infrastructure for scenario-based and environment-based testing.
• Conduct comparative analyses of model architectures, training procedures, and evaluation outcomes.
• Implement tools for continuous monitoring, regression testing, and quality assurance for ML systems.
• Design and execute stress tests and red-teaming workflows to uncover vulnerabilities and edge cases.
• Collaborate with operations teams and subject matter experts to produce high-quality evaluation datasets.
• Comfortable with light travel (approximately 10%) for customer interaction and team needs.

This role will require an active security clearance or the ability to obtain a security clearance.

Ideally you’d have:

• Experience in computer vision, deep learning, reinforcement learning, or NLP in production settings.
• Strong programming skills in Python; experience with TensorFlow or PyTorch.
• Background in algorithms, data structures, and object-oriented programming.
• Experience with LLM pipelines, simulation environments, or automated evaluation systems.
• Ability to convert research insights into measurable evaluation criteria.

Nice to haves:

• Graduate degree in CS, ML, or AI.
• Cloud experience (AWS, GCP) and model deployment experience.
• Experience with LLM evaluation, CV robustness, or RL validation.
• Knowledge of interpretability, adversarial robustness, or AI safety frameworks.
• Familiarity with ML evaluation frameworks and agentic model design.
• Experience in regulated, classified, or mission-critical ML domains.

The goal of a Senior Machine Learning Engineer at Scale is to leverage techniques in the fields of generative AI, computer vision, reinforcement learning, and agentic AI to improve Scale's products and customer experience in production environments. Our machine learning engineers take advantage of robust internal infrastructure and  unique access to massive datasets to deliver improvements to our customers.

Our Public Sector Machine Learning team is focused on deploying cutting-edge models to mission-critical government systems through products like Donovan and Thunderforge. Our work spans multiple modalities, with a strong focus on both large language models and computer vision. On the LLM side, we are developing agentic systems that help solve complex operational and planning challenges for government partners. This includes building agent frameworks that integrate with custom retrieval pipelines and production APIs, as well as evaluation tools to benchmark and refine agent behavior. We're also advancing research in areas like reinforcement learning for agentic LLMs, with successful deployment into real-world operational environments. On the computer vision front, we're training advanced models to increase labeling throughput and automate perception tasks. Our efforts include building large-scale fine-tuning pipelines, training models across multiple modalities, and developing generalizable vision foundation models to support a wide range of defense applications.

You will:

• Take state of the art models developed internally and from the community, use them in production to solve problems for our customers and taskers
• Improve and maintain production models through retraining, hyperparameter tuning, and architectural updates, while preserving core performance characteristics
• Collaborate with product and research teams to identify and prototype ML-driven product enhancements, including for upcoming product lines
• Work with massive datasets to develop both generic models as well as fine tune models for specific products
• Build scalable machine learning infrastructure to automate and optimize our ML services
• Serve as a cross-functional representative and advocate for machine learning techniques across engineering and product organizations
• Be comfortable learning new technologies quickly and managing multiple priorities in a fast-paced environment
• Comfortable with light travel (approximately 10%) for customer interaction and team needs
• This role will require an active security clearance or the ability to obtain a security clearance

Ideally You’d Have:

• Extensive experience with GenAI, Agentic AI, natural language processing, deep learning and deep reinforcement learning, or computer vision in a production environment
• Solid background in algorithms, data structures, and object-oriented programming
• Strong programing skills in Python, experience in Tensorflow or PyTorch

Nice to Haves:

• Graduate degree in Computer Science, Machine Learning or Artificial Intelligence specialization
• Experience working with cloud platforms (eg. AWS or GCP) and deploying machine learning models in cloud environments
• Experience with computer vision, generative AI models, large language models, or agentic systems
• Familiarity with ML evaluation frameworks and agentic model design

Join our Talent Community!

We’re always looking to connect with exceptional talent. If what we’re building resonates with you, we’d love to learn more about your background and what you’re looking to do next.

If you’d like to be considered for future opportunities with us, please submit your information below. This is an expression of interest, so while we may not be in touch immediately, your information will be kept on file and reviewed as new roles open up. In the meantime, we encourage you to follow us on LinkedIn and check our careers page for updates.

We are hiring across our U.S. and London hubs, and occasionally have remote opportunities as well. If you see a role that aligns with your experience, we recommend applying directly to that posting so our team can review your application as soon as possible.

What We're Looking For

Lightning AI is seeking a Senior Storage Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will focus on building and operating the storage systems that power large-scale AI/ML training, inference, and HPC workloads. You will work at the intersection of software, hardware, and operations—developing automation, improving reliability, and scaling distributed storage systems across our bare-metal infrastructure.

You will help own the data plane of our storage infrastructure, supporting high-throughput, low-latency data access for some of the most demanding AI workloads. You’ll play a key role in managing and evolving our storage stack (including VAST and S3-compatible systems like Ceph), ensuring performance, reliability, and efficiency at scale.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Storage Systems & Infrastructure

• Operate and scale distributed storage systems, including VAST and S3-compatible object storage (e.g., Ceph)
• Improve performance, reliability, and efficiency of storage systems supporting large-scale AI/ML workloads
• Troubleshoot complex storage and data path issues across hardware and software layers
• Optimize storage performance to support high-throughput, low-latency AI training and inference workloads

Automation & Tooling

• Build and maintain automation for provisioning, managing, and monitoring storage infrastructure
• Develop Python-based tools and workflows to reduce manual operational overhead
• Improve lifecycle management of storage clusters, from deployment through maintenance and scaling

Systems & Operations

• Manage and operate Linux-based systems in production, including bare-metal environments
• Partner with infrastructure and data center teams on hardware bring-up, upgrades, and issue resolution
• Support capacity planning, utilization tracking, and forecasting for storage systems
• Leverage monitoring and telemetry to diagnose issues and improve system performance and reliability

Cross-Functional Collaboration

• Work closely with Infrastructure Engineering, Network Engineering, and Platform teams to integrate storage into the broader platform
• Contribute to design discussions around new infrastructure deployments and scaling strategies
• Help define best practices for operating storage systems in high-performance computing environments

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Hands-on experience operating distributed storage systems (e.g., VAST, Ceph, or similar)
• Strong Linux systems experience in production environments
• Proficiency in Python or similar scripting/programming languages for automation
• Experience working with bare-metal infrastructure and hardware-oriented systems
• Ability to debug complex issues across system boundaries (storage, OS, hardware, networking)
• Experience with storage networking protocols (e.g., NFS or similar)
• Experience with capacity planning, monitoring, and performance tuning

Ideal Experience

• Experience with VAST storage systems in production environments
• Experience operating S3-compatible object storage at scale
• Data center operations experience, including working with physical hardware
• Familiarity with AI/ML or HPC workloads and their storage requirements
• Background in high-performance or low-latency distributed systems
• Familiarity with high-performance data transfer technologies (e.g., RDMA, GPU Direct Storage)
• Experience supporting GPU-based workloads or large-scale compute clusters

Compensation

What We’re Looking For

Lightning AI is seeking an Observability Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own and evolve observability systems across large-scale, GPU-enabled bare-metal infrastructure. You’ll operate at the intersection of infrastructure, data, and product, building platforms for metrics, logs, traces, and alerting that power both internal operations and customer-facing visibility.

You will play a key role in productizing observability, enabling scalable, multi-tenant monitoring experiences while keeping pace with rapid infrastructure buildouts. This includes designing telemetry pipelines, improving signal quality, and delivering actionable insights that ensure reliability and transparency across our platform.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

Observability Platform & Productization

• Own and evolve a scalable observability platform spanning metrics, logs, traces, and events
• Drive the productization of observability capabilities for both internal teams and external customers
• Design multi-tenant observability systems with scoped access, RBAC, and customer-facing visibility
• Continuously improve observability systems to keep pace with rapid infrastructure buildouts

Telemetry & Data Pipelines

• Design and operate telemetry pipelines ingesting data from GPUs, CPUs, networking (Ethernet & InfiniBand), containers, APIs, and BMC/Redfish
• Build systems to correlate signals across infrastructure layers to enable faster debugging and root cause analysis
• Implement streaming and real-time data pipelines using tools such as Kafka, OTEL, Promtail, or similar

Alerting, Reliability & Insights

• Design and implement noise-resistant alerting systems to improve signal quality and reduce operational load
• Create dashboards and alerting for InfraOps, Engineering, and Customer Success teams
• Build automated insights and enable proactive detection, forecasting, and system health visibility at scale

Systems & Infrastructure Engineering

• Contribute to broader infrastructure engineering projects beyond observability
• Partner with infrastructure and platform teams to embed observability into core systems and workflows
• Support large-scale, distributed systems across compute, networking, and storage environments

Cross-Functional Collaboration

• Work closely with customer-facing teams to deliver external observability experiences
• Collaborate with engineering, operations, and support teams to improve system transparency and reliability
• Help define best practices for observability across the organization

What You’ll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, SRE, or observability-focused roles
• Strong experience with monitoring systems such as Prometheus, Grafana, ELK, or VictoriaMetrics
• Experience building and operating observability platforms at scale
• Proficiency in Python, Go, or bash for automation and data integration
• Familiarity with containerized environments and Kubernetes observability
• Experience with streaming telemetry pipelines (Kafka, OTEL, Promtail, or equivalent)
• Experience with multi-tenant monitoring architectures
• Strong written and verbal communication skills

Ideal Experience

• Experience with GPU observability, particularly NVIDIA DCGM
• Experience monitoring large-scale GPU or HPC clusters
• Familiarity with InfiniBand fabric observability
• Experience building customer-facing or productized infrastructure systems
• Experience with correlation engines, RCA workflows, or predictive alerting systems
• Broad exposure to infrastructure domains including networking, storage, and provisioning

Compensation

What We're Looking For

Lightning AI is seeking a GPU & Compute Infrastructure Engineer to join our Infrastructure Engineering team.

In this role, you will own image management, system diagnostics, and validation across large-scale bare-metal compute infrastructure, with a particular focus on GPU-enabled systems. You will work at the intersection of hardware, systems, and software—developing automation, improving reliability, and enabling efficient cluster bring-up for AI/ML and HPC workloads.

You will play a key role in owning and evolving our image pipeline, running validation environments and test clusters, and supporting both system-level and GPU hardware qualification. This role is critical to ensuring that our infrastructure is consistent, performant, and ready to support demanding AI workloads from day one.

We’re flexible on location for this team. This role can work hybrid out of one of our US-based hubs (Seattle, NYC, or SF) or fully remote within the U.S., with occasional company and team offsites. We are not able to provide visa sponsorship for this position at this time.

What You'll Do

Systems, Image & Validation Infrastructure

• Own and evolve systems for image management, deployment, and validation across bare-metal infrastructure
• Run and maintain test clusters used for system validation, diagnostics, and bring-up
• Validate firmware, drivers, and OS images across compute and GPU-enabled systems
• Support hardware qualification efforts for next-generation platforms

GPU Diagnostics & Performance

• Own GPU diagnostics and validation workflows across large-scale infrastructure
• Diagnose and resolve complex issues across GPUs, drivers, OS, and hardware layers
• Analyze system and GPU performance using tools such as NVIDIA DCGM
• Identify failure patterns and drive improvements in system stability and validation coverage

Automation & Tooling

• Build and maintain automation for provisioning, validation, and system bring-up
• Develop Python-based tools and workflows to improve efficiency and reduce manual operational overhead
• Improve the reliability, repeatability, and scalability of image pipelines and validation systems

Systems & Operations

• Manage and operate Linux-based systems in production and validation environments
• Manage virtualization technology
• Support bare-metal provisioning workflows, including PXE and image-based systems
• Interface with hardware management systems (e.g., IPMI, Redfish) for monitoring and debugging

Cross-Functional Collaboration

• Partner with Infrastructure, Hardware, and Data Center teams on system bring-up and validation
• Collaborate with platform and ML teams to ensure systems meet workload requirements
• Contribute to best practices for provisioning, diagnostics, and lifecycle management of infrastructure

What You'll Need

Required Qualifications

• 5+ years of experience in infrastructure engineering, systems engineering, or related roles
• Strong Linux systems experience in production environments
• Hands-on experience with GPU-enabled systems and tools such as NVIDIA DCGM
• Familiarity with bare-metal provisioning and system bring-up workflows
• Proficiency in Python or similar scripting/programming languages for automation
• Ability to debug complex issues across hardware, OS, GPUs, and system software

Ideal Experience

• Experience with high-performance interconnects (e.g., InfiniBand, NVLink)
• Experience with PXE boot environments, LiveCD systems, or image-based provisioning workflows
• Experience with hardware management interfaces such as iDRAC, IPMI, or Redfish
• Data center operations experience, including working with physical hardware
• Experience supporting AI/ML or HPC workloads at scale
• Experience with GPU validation frameworks or large-scale hardware qualification processes

Compensation

What We're Looking For

We’re looking for a Fullstack Engineer to help develop and scale the Lightning AI platform across the frontend, CLI, APIs, and core backend systems. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in React and either Python or Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Proficiency in React and either Go (Golang) or Python, with a preference for Go
• Strong understanding of software engineering principles and lifecycle
• Hands-on experience as a Fullstack Engineer in a SaaS technology company
• Proven ability to take ownership of key features and drive end-to-end development
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

What We're Looking For

We’re looking for a Frontend Engineer to help develop and scale the UI and frontend infrastructure of the Lightning AI platform. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. With over 10,000 organizations building with Lightning, you’ll have a unique opportunity to impact how the world builds and deploys AI to production.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in React and Redux, and build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the user interface and frontend infrastructure while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain high standards for software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment in which each engineer can grow.

What You’ll Need

• Proficiency in React, JavaScript and TypeScript.
• Strong understanding of software engineering principles and lifecycle.
• Hands-on experience as a Frontend Engineer in a SaaS technology company.
• Proven ability to take ownership of key features and drive end-to-end development.
• Communication and collaboration with engineers, product managers, and designers.
• Ability to operate in high uncertainty and rapidly changing environments.

Compensation

What We're Looking For

We’re looking for a Backend Engineer to help develop and scale the Lightning AI platform, spanning APIs, infrastructure, billing, security, and integrations. In this role, you’ll take ownership of key features and drive them end-to-end, working closely with engineering, product, and design to ship high-quality, iterative improvements. This is an opportunity to build systems that support real-world machine learning workloads at scale.

This role is based in one of our hubs (Seattle, NYC, SF, or London), with a minimum of 2 in-office days per week and occasional team and company offsites. We are not able to provide visa sponsorship for this position at this time.

What You’ll Do

• Write readable/testable/efficient code in Go (Golang).
• Build deep expertise in our technology stack to deliver new features, improve system stability, and increase overall performance.
• Partner with engineering and product leaders on developing the Lightning product while using your experience to set the technical direction for large projects.
• Evaluate, strengthen, and document technical architecture, tools, and processes.
• Maintain software quality, implement automation, drive continuous delivery, and reduce time to production while proactively reducing technical debt.
• Mentor and coach engineers on system design, operating in high uncertainty, and problem-solving to create a supportive, inclusive environment where each engineer can grow.

What You’ll Need

• Extensive experience writing efficient, maintainable code in Go. Familiarity with best practices in testing, readability, and optimization is essential.
• Broad knowledge of backend and frontend systems, with experience building and scaling APIs, CLI tools, billing systems, and security protocols. Exposure to frontend frameworks is a plus.
• Experience with cloud platforms like AWS, GCP, or Azure and designing systems that are reliable, performant, and scalable. Familiarity with containerization (Docker, Kubernetes) is a strong advantage.
• Proven ability to take ownership of key features and drive end-to-end development
• Commitment to software quality, test automation, and continuous delivery. Experience proactively managing technical debt and speeding up time to production.
• Hands-on experience as a backend or product engineer in a SaaS technology company
• Communication and collaboration with engineers, product managers, and designers
• Ability to operate in high uncertainty and rapidly changing environments

Compensation

Expression of Interest

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

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

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

About the Role

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

The Opportunity

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

Expertise We Value:

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

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

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

Our Tech Stack:

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

How You Work: 

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

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

The Impact You’ll Be Contributing to Moloco:

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

The Opportunity:

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

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

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

ABOUT THE TEAM

Anduril’s Lattice software platform integrates together many sensors into a single cohesive view of the world, providing needed context for our users. AI Engineers on Anduril’s Frontier AI team build edge-compatible, generative AI systems into the Lattice software platform to provide features and products that improve autonomy and reduce cognitive burden on the warfighter. Specific applications include but are not limited to automating mission planning, battle-space understanding, voice-control of assets, and enabling higher-levels of autonomy. 

WHAT YOU'LL DO

• Distill and fine-tune transformer architectures so they can be deployed onto edge devices or compute denied environments
• Propose and prototype LLM-based Agentic systems that help solve real world problems, leveraging the latest state-of-the-art techniques in the field
• Develop and maintain mission relevant benchmarks
• Work cross-functionally with different business lines across Anduril to help discover and scope new research problems

REQUIRED QUALIFICATIONS

• BS in Computer Science, Machine Learning, Electrical Engineering, or related field
• 5+ years experience developing and benchmarking ML algorithms
• Experience pushing and maintaining ML algorithms in production
• Strong Python skills with experience in ML frameworks such as PyTorch
• Must be a U.S. Person due to required access to U.S. export controlled information or facilities

PREFERRED QUALIFICATIONS

• Experience fine-tuning transformer-based model
• Experience deploying deep-learning based models to edge devices or air gapped environments
• Prior experience in defense tech or start-up

ABOUT THE TEAM

Anduril Labs is a multidisciplinary team of technologists, solution architects, engineers, and military subject matter experts. Its mission is to drive innovation across all Anduril business units and product lines by developing novel concepts and next-generation technologies that enhance Anduril’s competitive edge and give its customers a decisive technological advantage over its adversaries.

ABOUT THE JOB

We are looking for a talented full stack software engineer to join our growing team at Anduril Labs in Washington, DC. As a full stack software engineer in Anduril Labs, you will help bring innovative, next-generation concepts to life through proof-of-concept development and rapid prototyping using bleeding edge technologies.

The ideal candidate has exceptional software development and creative problem-solving skills, is a self-starter, and can quickly grasp complex concepts. As a full stack software engineer, you possess the skills to architect, develop, and deploy distributed applications and services, including both front-end and back-end components. You have experience with agile, end-to-end software development lifecycle and are comfortable developing and deploying code across Windows and Linux-based systems (including standalone bare-metal hardware, virtualized environments, and cloud-hosted platforms). Embedded software development experience is a plus. You are also proficient in integrating legacy code and systems, leveraging open-source technologies, and developing and utilizing APIs. Additionally, you have a solid understanding of AI/ML core concepts (e.g., feature extraction, supervised vs. unsupervised learning, regression, classification, clustering, deep learning neural networks, NLP, LLMs, SLMs, model fine-tuning, prompt engineering, RAG) and hands-on experience developing (Gen)AI-enhanced applications or services.

We also expect candidates to have familiarity with database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB) and experience with data modeling, data wrangling, analytics, and visualization. Since Anduril Labs supports all Anduril businesses and product lines, you will have the unique opportunity to work closely with multi-disciplinary engineering and product development teams across the entire company. This means you will get to directly contribute to the development of Anduril’s next-generation products and services. So if you thrive in a dynamic environment that values creative problem-solving, love writing code, excel as both an individual contributor and team player, are eager to learn, and bring a can-do attitude, this role is for you.

WHAT YOU’LL DO

• Lead the development of prototypes to demonstrate advanced concepts in areas like autonomous and multi-agent systems, GenAI, advanced data analytics, quantum computing/sensing/networking/comms/machine learning, modeling, simulation, optimization, visualization, next-gen human-machine interfaces, heterogenous computing, and cybersecurity.
• Own the entire Software Development Lifecycle from inception through development, testing, deployment, and documentation for Anduril Labs-developed software prototypes.
• Interface and collaborate with other Anduril and customer engineering teams, and strategic partners.
• Support Anduril- and customer-funded R&D efforts.
• Participate in field experiments and technology demonstrations.

REQUIRED QUALIFICATIONS

• 3+ years of programming with Python, C++, Java, Rust, Go, or JavaScript/TypeScript.
• Proven software architecture and design skills.
• Ability to quickly understand and navigate complex systems and established codebases.
• AI/ML development using commercial and open-source AI frameworks, models, and tools (e.g., Jupyter Notebook, PyTorch, TensorFlow, Scikit-learn, OpenAI, Claude, Gemini, Llama, LangChain, YOLO, AWS Sagemaker, Bedrock, Azure AI, RAG).
• Web app development (e.g., React, Angular, or Vue).
• Cloud development (e.g., AWS, Azure, or GCP).
• Data modeling and wrangling.
• Networking basics (e.g., DNS, TCP/IP vs. UDP, socket communications, LDAP, Active Directory)
• Database technologies (e.g., SQL, NoSQL, Graph DB, Vector DB).
• API development and integration (e.g., REST, GraphQL).
• Containerization technologies (e.g., Docker, Kubernetes).
• Software development on Linux and Windows.
• Demonstrable hands-on experience using GenAI tools (e.g., OpenAI Codex, Claude Code, Gemini Code Assist, GitHub Copilot, Amazon CodeWhisperer, or similar) for software development, code generation, debugging, and algorithmic exploration.
• Experience with Git version control, build tools, and CI/CD pipelines.
• Demonstrated understanding and application of software testing principles and practices, including unit testing, integration testing, and end-to-end testing.
• Strong problem-solving skills, meticulous attention to detail, and the ability to work effectively in a collaborative team environment.
• Excellent communication and interpersonal skills, with the ability to effectively articulate complex technical concepts to diverse audiences.
• Eligible to obtain and maintain an active U.S. Top Secret SCI security clearance

PREFERRED QUALIFICATIONS

• BS in Computer Science, Engineering, or similar field.
• Distributed applications development (e.g., client/server, microservices, multi-agent solutions).
• High performance computing (HPC) and big data technologies (e.g., Apache Spark, Hadoop).
• Mobile app development (e.g., iOS or Android).
• Embedded software development experience.
• Willingness to travel up to approximately 10%

Hudson River Trading (HRT) is hiring an AI Researcher to join the HAIL team. HAIL (HRT AI Labs) is the team at HRT responsible for developing and maintaining our most powerful models, which are used by our trading teams to drive a significant fraction of our trading. We are building and deploying "foundation models for markets", that ingest and train on vast amounts of market data, to make predictions about future market state. We are seeking experienced AI researchers to join our team to accelerate our efforts.

Researchers have great independence to pursue the research directions they think would be most impactful as part of a small focused team with minimal bureaucracy. They are enabled by state-of-the-art research clusters with very high GPU-to-researcher ratios, and supported by excellent engineering, hardware, and systems teams to realize their vision. Your work will be directly, clearly, highly impactful on the business, and it will be challenging: this is a field with no easy or obvious solutions. You'll be responsible for improving every part of our models: from featurization of data, to architecture design, to training dynamics, to how trading decisions are made.

Qualifications

• Must have two or more years work experience in deep learning research, for any domain: robotics, biology, chemistry, physics, audio, video, etc.
• Experience translating methods between areas of application is highly valued.
• LLM experience is valuable, but not necessary.
• Strong engineering skills valued, especially any of: GPU kernel development, lower-level Pytorch/JAX development, intermediate C++, FPGA/ASIC experience, HPC experience.

The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. 

This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.

What We're Looking For

We are seeking a highly skilled Research Engineer to work on optimizing training and inference workloads on compute accelerators and clusters, through the Lightning Thunder compiler and the broader PyTorch Lightning ecosystem. This role sits at the intersection of deep learning research, compiler development, and large-scale system optimization. You’ll be shaping technology that pushes the boundaries of model performance and efficiency, creating foundational software that will impact the entire machine learning ecosystem.

This role is based in one of our hubs (NYC, SF, Seattle, or London), with a minimum of 2 in-office days per week and occasional team and company offsites.

What You'll Do

• Develop performance-oriented model optimizations at multiple levels:
• Graph-level (e.g., operator fusion, kernel scheduling, memory planning)
• Kernel-level (CUDA, Triton, custom operators for specialized hardware)
• System-level (distributed training across GPUs/TPUs, inference serving at scale)
• Advance the Thunder compiler by building optimization passes, graph transformations, and integration hooks to accelerate training and inference workloads.
• Work across the software stack to ensure optimizations are accessible to end users through clean APIs, automated tooling, and seamless integration with PyTorch Lightning.
  Design and implement profiling and debugging tools to analyze model execution, identify bottlenecks, and guide optimization strategies.
• Collaborate with hardware vendors and ecosystem partners to ensure Thunder runs efficiently across diverse backends (NVIDIA, AMD, TPU, specialized accelerators).
• Contribute to open-source projects by developing new features, improving documentation, and supporting community adoption.
• Engage with researchers and engineers in the community, providing guidance on performance tuning and advocating for Thunder as the go-to optimization layer in ML workflows.
• Work cross-functionally with Lightning’s product and engineering teams to ensure compiler and optimization improvements align with the broader product vision.

What You’ll Need

• Strong expertise with deep learning frameworks such as PyTorch
• Hands-on experience with model optimization techniques, including graph-level optimizations, quantization, pruning, mixed precision, or memory-efficient training.
• Knowledge of distributed systems and parallelism strategies (data/model/pipeline parallelism, checkpointing, elastic scaling).
• Familiarity with software engineering practices: designing APIs, building robust tooling, testing, CI/CD for performance-sensitive systems.
• Excellent collaboration and communication skills, with the ability to partner across research, engineering, and external contributors.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice-to-Haves

• Experience with CUDA, Triton, or other GPU programming models for developing custom kernels.
• Deep understanding of deep learning compiler internals (IR design, operator fusion, scheduling, optimization passes) or proven work in performance-critical software.
• Proven track record contributing to open-source projects in ML, HPC, or compiler domains.
• Advanced degree (Master’s or PhD) in machine learning, compilers, or systems highly preferred.

Compensation

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.

AI Office Lead - Senior AI Solutions Architect

NTT DATA is a team of more than 139,000 diverse professionals operating in more than 50 countries worldwide. Our sectors of activity include telecommunications, finance, industry, utilities, energy, public administration, and health.

Our mission? Offer technological solutions, business, strategy, development, and application maintenance while being a benchmark in consulting. Thanks to the collaboration between teams, the human quality of our people, and the fact that we do not conform to what is established, we always seek innovation that brings us closer to the future.

Our essence has led us to the forefront of technology, breaking paradigms and providing solutions that truly respond to each client's needs. Our talent has led us to be one of the top six technology companies in the world.

Because #Greattech, needs #GreatPeople, like you

NTT Data seeks high-achieving team players who quickly adapt to new challenges and entrepreneurial ventures. We are looking for a Senior AI Solutions Architect to work with our global client in Washington, D.C. This role will require an onsite presence at our client location.

Location: Washington D.C. onsite is highly preferred BUT open to candidates from Peru, Mexico, Brazil, or Chile who can work in the DC time zone**

Focus: AI Platform Architecture, Orchestration & Enterprise Integration
Experience Level: Senior (7+ years)

Role Overview

Background & Environment

• Proven experience as a senior architect or technical lead within AI, data, or digital platforms.
• Experience working in large, federated, or matrixed organizations, including public sector, healthcare, or international institutions.
• Strong background operating in environments with governance, compliance, interoperability, and cross-domain integration requirements

Key Responsibilities

Required Technical Skills & Expertise

Preferred Certifications & Training

• Scrum Master or equivalent Agile certification
• Executive-level training in AI Strategy
• NIST AI Risk Management Framework (AI RMF) training
• Microsoft Azure AI Engineer Associate
• Microsoft Azure Solutions Architect Expert
• Microsoft Copilot and Agent Administration Fundamentals

Why NTT Data?   

Empowerment and rewards are the cornerstone of our career development model. We are a young, fast-growing company, with a highly innovative and entrepreneurial spirit, because of this professional experience and growth will be unmatched. Our talent and positive attitude allow us to transform our goals into achievements, and projects into realities.

NTT Data is committed to hiring and retaining a diverse workforce. We are proud to be an Equal Opportunity/Affirmative Action-Employer, making decisions without regard to race, color, religion, creed, sex, sexual orientation, gender identity, marital status, national origin, age, veteran status, disability, or any other protected class. NTT Data is an Equal Opportunity Employer Male/Female/Disabled/Veteran and a VEVRAA Federal Contractor.

What We're Looking For

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

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

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

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

What You’ll Do

Secure AI and Machine Learning Systems

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

Application Security Engineering

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

Inference Platform Security

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

AI Supply Chain and Model Security

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

Security Automation and Tooling

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

What You'll Need

Required Experience

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

AI and Machine Learning Experience

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

It's a Strong Plus If You Have

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

What Success Looks Like

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

Why This Role Matters

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

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

Compensation

Who we are

The real world is the next frontier, and at Metropolis, we are creating the artificial intelligence to make it responsive. We are pioneering the Recognition Economy — a future where mundane repetition disappears and being known unlocks access, comfort and belonging everywhere you go. From transforming parking into a seamless drive-in, drive-out experience for millions of Members to expanding our intelligence layer across retail and hospitality, we are building a world that feels instinctive and magical. The future isn’t coming; it’s here, and we need builders, innovators and problem solvers to help us create it.

Who you are

Metropolis is seeking a Senior Manager of Machine Learning Engineering within the Advanced Technologies Group to lead the technical vision and execution of our foundational systems that power our next generation of AI. You will oversee 4 critical pillars within the Machine Learning org:data engineering, annotation pipelines, ML Infrastructure and Deployment of Agentic AI solutions. You are a hands-on, senior technical leader with a broad dynamic range, capable of providing high-level strategic direction while remaining technically proficient enough to dive into the weeds with your team. Your mission is to transition state-of-art models into robust, autonomous production systems that automate complex enterprise workflows.You will partner closely with internal engineering teams and external vendors to build the scalable tools and data pipelines that define the future of recognition economy.

What you'll do

• Build and maintain scalable, compliant and auditable data infrastructure to serve computer vision and AI pricing use cases 
• Build scalable data engineering pipelines and automated annotation workflows (LLM-in-the-loop) to reduce reliance on manual labeling and accelerate model iteration
• Own the MLOps lifecycle, including distributed training infrastructure, model registries, and low-latency inference services. Ensure high availability and observability for all deployed models
• Define technical direction, lead and grow a high-performance team of data and ML infrastructure engineers to influence impactful business outcomes
• Develop foundational systems to productionize agentic AI, Large Language Models (LLMs) and Vision Language Models (VLMs) solutions for workflow automation to enhance our products
• Enable Metropolis’s move into personalization and targeted advertisement through innovative ML data pipelines and feature stores
• Collaborate with external vendors and annotation platform providers to ensure high-quality data for production models
• Partner with other ML leaders (Growth , Edge deployment) and cross-functional leaders in Hardware, Platform, and Product engineering to align development roadmaps

What we're looking for

• 10+ years of professional experience in data and machine learning engineering with proven expertise in building enterprise-scale, auditable ETL pipelines and data governance mechanisms
• 5+ years of experience in leadership and management, ideally having managed other managers
• MS or PhD in computer science and/or a quantitative discipline
• Strong experience in distributed data processing like Apache Spark, Kafka, Cloud native data storage and processing services
• 1+ years experience building data /eval pipelines and deploying agentic AI solutions (LLMs and/or VLMs)
• Experience managing technical programs, defining milestones, and communicating progress to diverse audiences
• Familiarity with deep learning frameworks such as TensorFlow or PyTorch
• Strong proficiency with SQL and Python
• Engage effectively with external data providers and vendors
• Familiarity with computer vision systems and models (e.g. object detection, tracking, segmentation)

While not required, these are a plus:

• Manage large scale datasets and database tools for data processing
• Deploy ML services to the cloud with a focus on scalability and reliability
• Operate in innovative, high-growth environments

4 Days in Office: Metropolis values in-person collaboration to drive innovation, strengthen culture, and enhance the Member experience. Our corporate team members hold to our office-first model, which requires employees to be on-site at least four days a week, fostering organic interactions that spark creativity and connection

When you join Metropolis, you'll join a team of world-class product leaders and engineers, building an ecosystem of technologies at the intersection of parking, mobility, and real estate. Our goal is to build an inclusive culture where everyone has a voice and the best idea wins. You will play a key role in building and maintaining this culture as our organization grows. The anticipated base salary for this position is $200,000.00 USD to $250,000.00 USD annually. The actual base salary offered is determined by a number of variables, including, as appropriate, the applicant's qualifications for the position, years of relevant experience, distinctive skills, level of education attained, certifications or other professional licenses held, and the location of residence and/or place of employment. Base salary is one component of Metropolis’s total compensation package, which may also include access to or eligibility for healthcare benefits, a 401(k) plan, short-term and long-term disability coverage, basic life insurance, a lucrative stock option plan, bonus plans and more. #LI-AR1 #LI-Onsite

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

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

The impact you will have:

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

What we look for:

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

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

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.

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 Seattle, WA 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 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 Seattle, WA 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.

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

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

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

The impact you will have:

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

What we look for:

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

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

The work: 

• Develop MLOps frameworks and workflows for a variety of domains and applications 

• Deploy, maintain, and optimize ML models and data processes in a production environment  

• Develop custom AI/ML algorithms that translate into mission value 

• Conduct experiments, evaluate model performance, and fine-tune algorithms to improve accuracy and efficiency

• Collaborate with cross-functional teams to integrate AI/ML models into products and services

Here’s what you need: 

• Hands-on experience with scripting languages such as Python, JavaScript or Rust 

• Hands-on experience with developing machine learning models at scale from inception to business impact 

• Hands-on experience with any major deep learning framework and libraries (TensorFlow, PyTorch, HuggingFace) 

• Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC 

• Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP 

• Design and develop custom/novel architectures, define use cases, and develop methodology & benchmarks to evaluate different approaches 

• Experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment/s

• Experience working with and managing processing of large datasets and computational or analytic jobs  or in academic setting

• Experience monitoring and triaging issues with data processes and tools   

• US Citizenship (No Dual citizenship)

Bonus points if you have:  

• Advanced Degree in computer science, technology, engineering, mathematics (STEM) related field, with Ph.D. preferred, but not required  

Security Clearance: 

• Active Top Secret or TS/SCI or TS/SCI with polygraph Clearance

The work: 

• Develop, train, finetune and evaluate computer vision models in a wide range of topics, including geospatial, biometrics, 3D vision, semantic extraction, etc. 

• Deploy, maintain, and optimize ML models and data processes in a production environment  

• Develop custom Computer Vision (CV) algorithms that translate into mission value 

• Create tools to provide feedback from production ML models and data processes  

• Assist in the development and optimization of computer vision models using deep learning frameworks (e.g., PyTorch, TensorFlow). 

• Collaborate with other scientists and engineers to build and deploy models for tasks such as object detection, image segmentation, classification, and tracking

• Stay up to date with the latest research and advancements in the field of computer vision and deep learning

• Participate in data collection, preprocessing, and augmentation processes to ensure high-quality datasets

• Conduct experiments, analyze results, and contribute to the improvement of model accuracy and efficiency

• Assist in the integration of computer vision algorithms into production systems and applications 

• Document code, methodologies, and experimental results

Here’s what you need: 

• Hands-on experience with computer vision libraries (e.g., OpenCV) and deep learning frameworks (e.g., PyTorch, TensorFlow)

• Proficiency with programming languages such as Python, C/C++ or Rust 

• Strong understanding of CNNs, transformers and other advanced architectures and their applications in computer vision tasks

• Strong analytical and problem-solving skills

• Ability to work collaboratively in a team environment and take direction from senior team members

• Hands-on experience with developing computer vision models at scale from inception to business impact 

• Design and develop custom/novel architectures, define use cases, and develop methodology & benchmarks to evaluate different approaches 

• U.S. Citizenship (No Dual citizenship)

Bonus points if you have:  

• Advanced Degree in computer science, technology, engineering, mathematics (STEM) related field, with Ph.D. preferred, but not required 
• Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC
• Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP
• Hands on experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment 
• Hands-on experience with other image modalities (SAR, IR, HSI, Lidar, Sonar) 

Security Clearance: 

• Active Top Secret or TS/SCI or TS/SCI with polygraph Clearance

The work: 

• Develop MLOps frameworks and workflows for a variety of domains and applications 

• Deploy, maintain, and optimize ML models and data processes in a production environment  

• Develop custom AI/ML algorithms that translate into mission value 

• Conduct experiments, evaluate model performance, and fine-tune algorithms to improve accuracy and efficiency

• Collaborate with cross-functional teams to integrate AI/ML models into products and services

Here’s what you need: 

• Hands-on experience with scripting languages such as Python, Javascript or Rust 

• Hands-on experience with developing machine learning models at scale from inception to business impact 

• Hands-on experience with any major deep learning framework and libraries (Tensorflow, PyTorch, HuggingFace) 

• Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB, Airflow, Kubeflow, Gitlab CI or DVC 

• Hands-on experience developing and deploying machine learning pipelines in AWS, Azure or GCP 

• Design and develop custom/novel architectures, define use cases, and develop methodology & benchmarks to evaluate different approaches 

• Experience deploying, maintaining, testing, and optimizing ML models and data platforms in a production environment  

• Experience working with and managing processing of large datasets and computational or analytic jobs  

• Experience monitoring and triaging issues with data processes and tools   

• Must be a U.S. Citizen (No Dual citizenship)

Bonus points if you have:  

• Advanced Degree in computer science, technology, engineering, mathematics (STEM) related field, with Ph.D. preferred, but not required  

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

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

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

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

The impact you will have:

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

What we look for:

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

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

Your Impact

We are seeking a skilled and innovative Senior AI Research Scientist to join a new team focusing on agentic video and multimodal reasoning systems. As a research scientist at Axon you will play a crucial role in developing AI solutions that transform both the enterprise and public safety domains and support our company’s mission: accelerate justice, protect truth, and save lives. You will advance the state-of-the-art in machine learning and multimodal technology and apply your research findings to create new responsible AI capabilities for Axon products. You will collaborate with product managers, engineers and cross-functional teams to train models and develop cutting-edge algorithms and solutions that enable intelligent perception and understanding of visual and multimodal data.

At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

What You’ll Do

Reports to: Director of AI Research
Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

• Collaborate with other scientists, engineers and product managers to build proof-of-concepts to shape the Axon of tomorrow.
• Lead end-to-end research efforts in AI-assisted universal search of and reasoning over large multimodal data with an emphasis on video understanding.
• Advance related computer vision, machine learning and gen-AI techniques for cloud and devices from multimodal data sources, including scene understanding, action recognition and anomaly detection.
• Design and implement responsible, privacy-preserving, efficient and scalable models for inference and analysis of visual data.
• Develop performance and quality metrics for agentic multimodal reasoning models and systems, and validate their effectiveness in real-world settings.
• Stay up-to-date with the latest research and advances in agentic AI, machine learning and computer vision and translate relevant findings into shipping Axon products.
• Contribute to academic publications, technical documentation, and patent disclosures to share insights and findings with the broader community.
• Coach and mentor junior scientists.

What You Bring

• PhD and 3+ years of experience in Computer Science or a related field with a focus on multimodal machine learning, large language models, video understanding, information retrieval, agentic reasoning or related technical fields.
• Proven track record of applied research and/or production impact in multimodal learning, video-language modeling, retrieval systems, foundation models, agentic systems, or RAG architectures.
• Experience owning and driving the ML development lifecycle from problem definition and data strategy through model development, evaluation, deployment, and iteration in production environments.
• Experience contributing to large-scale ML and multimodal RAG systems including embeddings, indexing and vector search at scale, distributed training or inference workflows, evaluation and ranking optimization, agentic tool use, and grounding LLMs with external knowledge.
• Strong understanding of video analysis and temporal modeling as well as computer vision fundamentals and trade-offs.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Proficiency in Python and frameworks such as PyTorch, TensorFlow or Keras.
• 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

The Pay: Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The starting base pay for this role is between USD 159,750 in the lowest geographic market and USD 234,300 in the highest geographic market. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit www.axon.com/careers/benefits.

#LI-Hybrid

Data Scientist 

Location: Woodinville, WA

Details: Hybrid 

Redapt Inc. is a pioneering world-class data center infrastructure integrator, technology engineering firm, and cloud services provider. Our teams focus on delivering innovative solutions and services that power our customers' most demanding applications and enable them to extract powerful insights from data that drive true business value.   

We are looking for a versatile AI/ML Engineer who can lead, sell, design, and implement modern architecture for a diverse set of customers and industries. The ideal candidate would have deep experience in designing high-value advanced analytics solutions utilizing popular analytical frameworks running on Azure, GCP, and AWS. This position will be responsible for leading customer conversations, creating and presenting project architecture, and leading delivery.

Primary responsibilities include mentoring and leading other consultants, leading pre-sales workshops with finance and technology executives to uncover innovative ways to apply advanced analytics techniques to solve business problems in new ways. The role can be hands-on when necessary but should have Direct delivery experience to recommend technologies, solutions, and help troubleshoot.    

Responsibilities: 

• Drive growth through business development, resourcing, and quality delivery. 

• Monitor business impact and value generation of analytics projects. 

• Help create go-to-market strategies around advanced AI/ML Services and hardware. 

• This role will be directly involved in the business development process, delivering customer demos to show the value of how data can drive business goals. 

• Create proposals and SOWs. 

• Work closely with sales and other practice leaders to recommend strategies to grow our data science services. 

• Manage full sales cycles, end-to-end, for high potential clients. 

• Evaluate business impact and priority initiatives for our portfolio of managed analytics customers.  

• Talent Leadership and Product Ownership. 

• Help with planning and staffing for data science projects. 

• Provide support for project managers through developing tasks, estimates, and dependencies to meet expectations. 

• Train the data science team on best practices and new technology initiatives.  

• Anticipate the impact of new technologies and frameworks and help create compelling data science offerings to our clients. 

Skills you bring with you: 

• Knowledge of how to use data science/AI/ML techniques in operations to impact corporate financials.  

• Working knowledge of DevOps process (CI/CD) applied to data science and ML ops. 

Qualifications: 

• Bachelor’s or Master’s Degree in Advanced Math, Data Science, or Computer Science.  

• 5-8+ years of experience with advanced data science techniques, frameworks, libraries, and technologies including but not limited to: 

• Tensorflow, KubeFlow, Python, R, Keras, NumPY, SciKit, PyTorch, SQL.
  
  
• Azure ML, Vertex AI, SageMaker, Databricks, Big query/Redshift/Snowflake
  
  
• ELT/ELT/Pipeline Design, Data Modeling, Spark, Airflow/DBT and API Integration Patterns

Nice to have: 

• LLM’s, RAG, Vector Databases, Prompt Evaluation, GenAI Solution Patterns 

The base salary range for this full-time position in the US is $130,000 - $140,000 annually + bonuses + benefits.  Redapt salary ranges are determined by role, level, and location.  The salary range displayed in each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations.  Please note, the base pay offered may vary within the range depending on a wide array of factors including but not limited to work location, job related knowledge/skills, relevant education/training, and level of experience.  Please note that the compensation details listed in the US role postings reflect the base salary only, and do not include bonuses or benefits. 

Equal Employment Opportunity: 

Redapt is an equal opportunity employer. Applicants will not be discriminated against because of race, color, creed, sex, sexual orientation, gender identity or expression, age, religion, national origin, citizenship status, disability, ancestry, marital status, veteran status, medical condition, or any protected category prohibited by local, state, or federal laws. All employment is decided based on qualifications, merit, and business need. 

#LI-TS1

We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end.

Main Responsibilities

• Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform.
• Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows.
• Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role.
• Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow.
• Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup.
• Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices.
• Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI.
• Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams.
• Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI.
• As part of our team, you will have the opportunity to work on all aspects of complex National Security problems.
• Annual travel up to 25%.

Preferred Qualifications

• B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.
• 3+ years of customer-facing experience in the design and implementation of AI/ML solutions.
• Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow).
• Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI).
• Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.
• Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
• Ability to work in a fast-paced environment and balance priorities across multiple projects at once.
• Experience reviewing and drafting responses to federal Requests for Comment (RFCs), Requests for Information (RFIs), Requests for Proposals (RFPs), etc. is preferred
• Experience working across the Civilian, DOD and NATSEC agencies, inclusive of experience in Federal Law Enforcement, Healthcare, Financial/Regulatory and Military operations and logistics
• Candidates must have an active TS (Top Secret) Clearance

Compensation range $170K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Locations

#LI-CG1

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform.

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy.

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources, and applying ML to enrich our datasets with predictive and generative intelligence. As a senior engineer, you will take ownership of key technical components and ensure that our systems meet the highest standards of performance, reliability, and security.

Primary Job Responsibilities:

• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards
• Support a culture of technical excellence by mentoring peers, sharing knowledge, and participating in code and design reviews. Promote innovation and continuous improvement through collaborative engineering practices
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested

Skills and Qualifications:

• Bachelor’s or advanced degree in Computer Science, Mathematics, Data Science, or a related technical field, advanced degree preferred
• 6+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus
• Deep proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $170,000-$240,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us! 

As a Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook’s wealth of structured and unstructured data including reports, news, and other textual content. This role requires deep technical expertise in advanced data analytics and machine learning, as well as a hands-on approach to designing, building, and optimizing ML solutions that power user-facing features on the PitchBook Platform. 

You will be deeply involved in the end-to-end development and operationalization of ML models, including their architecture, training, deployment, and ongoing maintenance. Your focus will span across natural language processing (NLP), generative AI (GenAI), large language models (LLMs), and scalable data systems. You will be expected to tackle complex technical challenges, contribute to architectural decisions, and collaborate closely with other engineers, data scientists, and product managers to ensure that your work aligns with business goals and AI/ML strategy. 

Your contributions will help unlock unique value for PitchBook customers by improving the speed, discoverability, quality, and quantity of insights available on the platform. This includes developing models that can infer meaning and structure from millions of discrete data sources and applying ML to enrich our datasets with predictive and generative intelligence.  

Primary Job Responsibilities:

• Deliver high-impact AI and ML capabilities that drive insight generation on the PitchBook Platform. Ensure your work contributes to broader business goals and is aligned with the team's strategic priorities 
• Provide hands-on expertise in designing, building, and deploying AI/ML models and services with a focus on NLP, summarization, semantic search, classification, and prediction. Contribute to the development of scalable, high-performance systems that meet production-grade reliability and efficiency standards 
• Contribute to a culture of technical excellence by sharing knowledge, pairing with teammates, and actively participating in code and design reviews. Provide situational guidance to junior engineers and contribute to team best practices 
• Build and optimize models that leverage classifiers, transformers, LLMs, and other NLP techniques to generate meaningful insights from structured and unstructured data. Integrate these models into the broader AI/ML infrastructure in collaboration with partner teams
• Collaborate with engineering, product management, and data collection teams to ensure models are informed by high-quality data and support strategic product goals
• Explore and experiment with emerging technologies, methodologies, and tools in the fields of GenAI, NLP, and search. Translate research findings into practical solutions that enhance PitchBook’s AI capabilities 
• Contribute to best practices in model transparency, monitoring, evaluation, and compliance. Help maintain high standards of security, data integrity, and responsible AI use across your projects 
• Participate in the technical evaluation of candidates and help onboard new team members by contributing to documentation, pairing, and knowledge-sharing practices 
• Apply principles from Agile, Lean, and Fast-Flow methodologies to support efficient model development and deployment cycles 
• Support the vision and values of the company through role modeling and encouraging desired behaviors
• Participate in various company initiatives and projects as requested   

Skills and Qualifications:

• Bachelor’s degree in Computer Science, Mathematics, Data Science, or related technical field, advanced degrees are preferred 
• 2+ years of experience in software engineering or machine learning engineering, with a strong focus on AI/ML applications in insight generation, summarization, semantic search, and prediction 
• Demonstrated expertise in natural language processing (NLP) and machine learning, including hands-on experience with classifiers, transformer models, large language models (LLMs), and widely used ML and data science libraries such as scikit-learn, pandas, numpy, TensorFlow, and PyTorch
• Experience delivering production-grade GenAI or LLM-based systems with measurable business impact 
• Familiarity with the LangChain ecosystem, including tools such as LangSmith and LangGraph, and experience using them in production environments is a strong plus 
• Proficiency in building and maintaining scalable data pipelines and distributed systems using technologies such as Apache Kafka, Airflow, and cloud data platforms like Snowflake 
• Strong programming skills in Python and SQL, with working knowledge of additional languages such as Java or Scala considered a plus
• Practical experience with cloud-native development, containerization, and orchestration technologies such as Docker and Kubernetes
• Demonstrated ability to solve complex technical problems, contribute to architectural decisions, and deliver high-performance, reliable solutions
• Excellent communication and collaboration skills, with experience working cross-functionally with product managers, engineers, and data scientists in globally distributed teams
• Experience working in fast-paced, data-driven environments. Prior exposure to fintech or financial data platforms is a strong advantage
• Experience authoring research papers for peer-reviewed AI/ML conferences (e.g., NeurIPS, ICML, ACL) and participating in the broader AI research community is strongly preferred 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health

• Comprehensive health benefits
• Additional medical wellness incentives
• STD, LTD, AD&D, and life insurance

Emotional Health

• Paid sabbatical program after four years
• Paid family and paternity leave
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend
• Robust training programs on industry and soft skills
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program
• Monthly transportation stipend

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $125,000-$180,000
• Target annual bonus percentage: 10%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week.

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-MS1

#LI-Onsite

About the Role:

As a member of the Product and Engineering team at PitchBook, you will be part of a team of big thinkers, innovators, and problem solvers who strive to deepen the positive impact we have on our customers and our company every day. We value curiosity and the drive to find better ways of doing things. We thrive on customer empathy, which remains our focus when creating excellent customer experiences through product innovation.

We know that greatness is achieved through collaboration and diverse points of view, so we work closely with partners around the globe. As a team, we assume positive intent in each other’s words and actions, value constructive discussions, and foster a respectful working environment built on integrity, growth, and business value. We invest heavily in our people, who are eager to learn and constantly improve. Join our team and grow with us!

As an Engineering Manager, Machine Learning (ML) Operations in the Technology & Engineering division, you will be responsible for leading and managing PitchBook’s MLOps team. The team is responsible for enabling PitchBook’s Machine Learning teams and practitioners by providing tools and golden paths that optimize all aspects of the Machine Learning Development Life Cycle (MLDLC). Your team’s work will support projects in a variety of domains, including Generative AI (GenAI), Large Language Models (LLMs), Natural Language Processing (NLP), Classification, and Regression. Your role will be critical in driving AI (Artificial Intelligence) innovations across the organization.

Primary Job Responsibilities:

• Lead the MLOps team direction and execution (operations, processes, practices, and standards), working closely with engineering leadership and product management to craft roadmaps, define KPIs, and achieve success criteria
• Ensure effective communication and coordination across geographically dispersed teams. Oversee the enablement of scalable solutions that meet high standards of reliability and efficiency
• Champion the adoption and integration of ML best practices at PitchBook, fostering a culture of innovation and experimentation to drive the development of high-quality AI products
• Serve as a force multiplier by removing roadblocks, implementing process improvements, providing frequent and actionable feedback to team members, and building practices for ideation and innovation
• Bridge the gap between business/product needs and execution, including building and delivering on group-level objectives and key results, identifying resource needs, and building execution plans for initiatives
• Ensure MLOps roadmap items are delivered on time and have exceptional quality
• Learn constantly and be passionate about discovering new tools, technologies, libraries, and frameworks (commercial and open source), that can be leveraged to improve PitchBook’s AI capabilities
• Describe technical content in intuitive ways for a variety of audiences, adapting communication from highly technical deep dives with engineers to non-technical dialogue with executive stakeholders
• Establish and drive a culture founded on creating belonging, psychological safety, candor, connection, cooperation, and fun
• Understand how to apply agile, lean, and principles of fast flow to team efficiency and productivity 
• Support the vision and values of the company through role modeling and encouraging desired behaviors 
• Participate in various company initiatives and projects as requested 

Skills and Qualifications:

• Bachelor’s, Master’s, or PhD in Computer Science, Mathematics, Data Science, or a related field
• 3+ years of experience in an engineering leadership role, managing globally distributed teams
• 6+ years of experience in hands-on development of Machine Learning algorithms
• 6+ years of experience in hands-on deployment of Machine Learning services
• 6+ years of experience supporting the entire MLDLC, including post-deployment operations such as monitoring and maintenance
• 6+ years of experience with Amazon Web Services (AWS) and/or Google Cloud Platform (GCP)
• Experience with at least 70%: PyTorch, Tensorflow, LangChain, scikit-learn, Redis, Elasticsearch, Amazon SageMaker, Google Vertex AI, Weights & Biases, FastAPI, Prometheus, Grafana, Apache Kafka, Apache Airflow, MLflow, and KubeFlow
• Ability to break large, complex problems into well-defined steps, ensuring iterative development and continuous improvement
• Experience in cloud-native delivery with a deep practical understanding of containerization technologies such as Kubernetes and Docker, and the ability to manage these across different regions
• Proficiency in GitOps and creation/management of CI/CD pipelines
• Demonstrated experience building and using SQL/NoSQL databases
• Demonstrated experience with Python (Java is a plus) and other relevant programming languages and tools
• Excellent problem-solving skills with a focus on innovation, efficiency, and scalability in a global context
• Strong communication and collaboration skills, with the ability to engage effectively with internal customers across various cultures and regions
• Ability to be a team player who can also work independently
• Experience working across multiple development teams is a plus
• Proficiency with the Microsoft Office suite including in-depth knowledge of Outlook, Word, and Excel with the ability to pick up new systems and software easily 
• Must be authorized to work in the United States without the need for visa sponsorship now or in the future

Benefits + Compensation at PitchBook:

Physical Health            

• Comprehensive health benefits
• Additional medical wellness incentives 
• STD, LTD, AD&D, and life insurance

Emotional Health 

• Paid sabbatical program after four years
• Paid family and paternity leave 
• Annual educational stipend
• Ability to apply for tuition reimbursement
• CFA exam stipend 
• Robust training programs on industry and soft skills 
• Employee assistance program
• Generous allotment of vacation days, sick days, and volunteer days 

Social Health 

• Matching gifts program
• Employee resource groups
• Subsidized emergency childcare  
• Dependent Care FSA
• Company-wide events
• Employee referral bonus program  
• Quarterly team building events

Financial Health 

• 401k match
• Shared ownership employee stock program 
• Monthly transportation stipend  

*Please be aware the above PitchBook benefit and perk offerings are subject to corresponding plan and policy documents and may change during the course of your employment.

Compensation

• Annual base salary: $240,000-$300,000
• Target annual bonus percentage: 15%

Working Conditions:

At the heart of our company is a belief in the power of in-person collaboration. Being together in the office fuels our creativity, strengthens our connections, and drives the innovation that sets us apart. Our culture is built on spontaneous moments—those hallway conversations, whiteboard brainstorms, and shared celebrations in each of our global offices—that simply can’t be replicated remotely. This role is expected to be in the office 5 days a week. 

The job conditions for this position are in a standard office setting. Employees in this position use PC and phone on an on-going basis throughout the day. Limited corporate travel may be required to remote offices or other business meetings and events.

We are excited to get to know you and your background. Concerned that you might not meet every requirement? We encourage you to still apply as you might be the right candidate for the role or other roles at PitchBook.

#LI-TK1

#LI-Onsite

Your Impact

Are you passionate about AI? Do you love engineering solutions enabling fast, cutting-edge science? Are you eager to contribute to building products impacting the world for the greater good?

As a ML Engineer at Axon, you will contribute to architecting and implementing the platform used by Axon scientists to bring safe, secure, reliable AI features to Axon devices. Collaborating closely with scientists and device engineers, you will enable new AI capabilities for Axon products (Fleet, Axon Body, Axon Air, and more). You will also make sure As part of a multidisciplinary team, you will be exposed to a wide range of domains and applications: from Automatic License Plates Recognition to Object Tracking and Automatic Speech Recognition.

The ideal candidate will have a consistent track record of successfully optimizing models for the edge and deploying AI models at the edge, including on device with limited memory & connectivity, to serve users world wide. They will understand the AI lifecycle and be capable of supporting scientists end-to-end along the development of a new machine learning models and AI capabilities, leading to better and more responsible AI solutions. They are willing to be bold and stand up to support the team in enabling features transforming the life of officers, and driving a positive impact in the public safety space.

What You’ll Do

Location: Hybrid from Seattle, WA
Reports to: Senior Director, AI Platform Engineering
Direct Reports:

• Architect and develop secure, privacy-preserving, on device solutions to enable the continuous improvement of existing AI models.
• Collaborate with scientists in architecting and implementing state-of-the-art edge distributed training techniques.
• Implement on device monitoring solutions used for continuous model improvement
• Implement innovative model compression solutions to enable AI at the edge.
• Impact the team by bringing your own expertise and deep knowledge of the state-of-the-art to introduce new techniques leading to tangible impact in terms of model fairness, performance, and platform scalability.

What You Bring

• Bachelor’s Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
• 10+ years of software engineering experience and a proven track record of successfully architecting and maintaining large-scale distributed platforms.
• Experience with AI on chips, on device model deployment and management.
• Proficiency in python, C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
• Advanced knowledge and hands-on experience with on chips development.
• Excellent problem solving skills and ability to dive into system architecture, design, performance metrics, code, test plans, project plans, deployments and operations
• Comfort communicating and interacting with scientists, engineers and product managers.

Preferred

• Master’s Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
• Hands-on experience in solving Computer Vision or Natural Language Understanding problems in a business setting.
• Familiarity with responsible AI, de-biasing, model encryption and de-identification techniques.

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
• Employee Resource Groups (ERGs)
• 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 Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid

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 Scottsdale, AZ 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

Are you passionate about AI? Do you love engineering solutions enabling fast, cutting-edge science? Are you eager to contribute to building products impacting the world for the greater good?

As a Principal ML Engineer at Dedrone, you will contribute to architecting and implementing the platform used by Dedrone scientists to bring safe, secure, reliable AI features to the field of counter UAS devices. Collaborating closely with scientists and software engineers, you will enable new AI capabilities for Dedrone products. As part of a multidisciplinary team, you will be exposed to a wide range of domains and applications: from Multi-modal Sensor Fusion to Real Time Systems with distributed edge compute.

The ideal candidate will have a consistent track record of successfully optimizing models for the edge and deploying AI models at the edge, including on device with limited memory & connectivity, to serve users world wide. They will understand the AI lifecycle and be capable of supporting scientists end-to-end along the development of new machine learning models and AI capabilities, leading to better and more responsible AI solutions. They are willing to be bold and stand up to support the team in enabling drone safety measures across Public Safety, Enterprise and Defense domains.

What You’ll Do

Location: Hybrid from Seattle, WA
Reports to: VP, Dedrone Engineerin

• Architect and develop secure, privacy-preserving, on device solutions to enable the continuous improvement of existing AI models.
• Collaborate with scientists in architecting and implementing state-of-the-art edge distributed training techniques.
• Implement on device monitoring solutions used for continuous model improvement
• Implement innovative model compression solutions to enable AI at the edge.
• Impact the team by bringing your own expertise and deep knowledge of the state-of-the-art to introduce new techniques leading to tangible impact in terms of model fairness, performance, and platform scalability.

What You Bring

• Bachelor’s Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
• 13+ years of software engineering experience and a proven track record of successfully architecting and maintaining large-scale distributed platforms.
• Experience with AI on chips, on device model deployment and management.
• Proficiency in python, C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
• Advanced knowledge and hands-on experience with on chips development.
• Excellent problem solving skills and ability to dive into system architecture, design, performance metrics, code, test plans, project plans, deployments and operations
• Comfort communicating and interacting with scientists, engineers and product managers.

Preferred

• Master’s Degree or PhD in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
• Hands-on experience in solving Computer Vision or Natural Language Understanding problems in a business setting.
• Familiarity with responsible AI, de-biasing, model encryption and de-identification techniques.

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
• Employee Resource Groups (ERGs)
• 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 Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid

Your Impact

We are seeking a skilled and innovative Senior Research Scientist to join one of our AI teams focusing on computer vision and machine learning (CVML). As a research scientist at Axon you will play a crucial role in developing AI solutions that transform both the enterprise and public safety domains and support our company’s mission: accelerate justice, protect truth, and save lives. You will advance the state-of-the-art in CVML and multimodal technology and apply your research findings to create new responsible AI capabilities for Axon products. You will collaborate with product managers, engineers and cross-functional teams to train models and develop cutting-edge algorithms and solutions that enable intelligent perception and understanding of visual data.

At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

What You’ll Do

Reports to: Director of AI Research
Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

• Collaborate with other scientists, engineers and product managers to build proof-of-concepts to shape the Axon of tomorrow.
• Lead end-to-end research efforts in advanced computer vision, machine learning and gen-AI techniques for cloud and devices from multimodal data sources, including scene understanding, action recognition and anomaly detection.
• Design and implement responsible, privacy-preserving, efficient and scalable models for inference and analysis of visual data.
• Develop performance and quality metrics for CVML models and systems, and validate their effectiveness in real-world settings.
• Optimize algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Stay up-to-date with the latest research and advances in CVML and translate relevant findings into shipping Axon products.
• Contribute to academic publications, technical documentation, and patent disclosures to share insights and findings with the broader community.
• Coach and mentor junior scientists.

What You Bring

• PhD and 3+ years experience in Computer Science or a related field with a focus on computer vision, machine learning, artificial intelligence or related technical fields.
• Proven track record of research in machine learning, computer vision or related fields.
• Experience driving the ML development lifecycle and leveraging state-of-the-art research to deliver high quality models at scale.
• Strong computer vision fundamentals such as image processing, feature extractions, object detection, semantic segmentation, video analysis or action recognition.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Proficiency in Python and frameworks such as PyTorch, TensorFlow or Keras.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.
• Experience in developing computer vision algorithms for resource-constrained edge devices or embedded systems preferred but optional.

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

The Pay: Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The starting base pay for this role is between USD 159,750 in the lowest geographic market and USD 234,300 in the highest geographic market. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit www.axon.com/careers/benefits.

#LI-Hybrid

Your Impact 

Are you eager to contribute to building AI products impacting the world for the greater good?

As an ML Engineer at Axon, you will contribute to developing AI solutions transforming the public safety space and supporting our company’s mission: accelerate justice, protect truth, and save lives. Working closely with other ML engineers and scientists, you will enable new AI capabilities for Axon’s products (Fleet, Draft One, Axon Air, VR and more) by supporting the training, evaluation, testing and deployment of machine learning models on Axon devices and cloud.

As part of a multidisciplinary team, you will be exposed to a wide range of AI domains and applications: from computer vision to speech recognition and natural language understanding.

What You’ll Do

Location: Hybrid from our office in Seattle, Washington. 
Reports to: Manager, Machine Learning Engineering

• Collaborate with scientists and product managers to build proof-of-concepts (POCs) contributing to shaping the Axon of tomorrow.
• Architect and develop secure, privacy-preserving, solutions to enable the continuous improvement of existing AI models.
• Architect platforms that accelerate research and AI product development.
• Collaborate with scientists in architecting and implementing state-of-the-art training techniques.
• Set high standards for ethical and responsible AI development.

What You Bring

• Bachelor’s Degree in Computer Science, Engineering, Electronics, Mathematics or an equivalent highly technical field.
• 6+ years of software engineering experience and a proven track record of successfully deploying AI models to the cloud.
• Experience with Infrastructure-as-code and cloud architecture.
• Proficiency in Python and C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
• Advanced knowledge and hands-on experience with Linux.
• Excellent problem solving skills and ability to dive deep into system architecture.
• Excellent software design skills.
• Comfort communicating and interacting with scientists, engineers and product managers.

What You Bring

• Master’s Degree/PhD in Computer Science, Engineering, Electronics, Mathematics or an equivalent highly technical field.
• Experience with LLMOps - evaluation, monitoring, quantization, teacher-learner, etc.).
• Hands-on experience with fine-tuning large parameter models.
• Familiarity with model encryption and privacy preserving AI techniques.

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 Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid

Your Impact 

Are you eager to contribute to building AI products impacting the world for the greater good?

As an ML Engineer at Axon, you will contribute to developing AI solutions transforming the public safety space and supporting our company’s mission: accelerate justice, protect truth, and save lives. Working closely with other ML engineers and scientists, you will enable new AI capabilities for Axon’s products (Fleet, Draft One, Axon Air, VR and more) by supporting the training, evaluation, testing and deployment of machine learning models on Axon devices and cloud.

As part of a multidisciplinary team, you will be exposed to a wide range of AI domains and applications: from computer vision to speech recognition and natural language understanding.

What You’ll Do

Location: Hybrid from our office in San Francisco, CA. 
Reports to: Manager, Machine Learning Engineering

• Collaborate with scientists and product managers to build proof-of-concepts (POCs) contributing to shaping the Axon of tomorrow.
• Architect and develop secure, privacy-preserving, solutions to enable the continuous improvement of existing AI models.
• Architect platforms that accelerate research and AI product development.
• Collaborate with scientists in architecting and implementing state-of-the-art training techniques.
• Set high standards for ethical and responsible AI development.

What You Bring

• Bachelor’s Degree in Computer Science, Engineering, Electronics, Mathematics or an equivalent highly technical field.
• 6+ years of software engineering experience and a proven track record of successfully deploying AI models to the cloud.
• Experience with Infrastructure-as-code and cloud architecture.
• Proficiency in Python and C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
• Advanced knowledge and hands-on experience with Linux.
• Excellent problem solving skills and ability to dive deep into system architecture.
• Excellent software design skills.
• Comfort communicating and interacting with scientists, engineers and product managers.

What You Bring

• Master’s Degree/PhD in Computer Science, Engineering, Electronics, Mathematics or an equivalent highly technical field.
• Experience with LLMOps - evaluation, monitoring, quantization, teacher-learner, etc.).
• Hands-on experience with fine-tuning large parameter models.
• Familiarity with model encryption and privacy preserving AI techniques.

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 San Francisco, CA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid

About the team

The Ranking & Relevance team’s mission is to help every patient find the right provider for their needs. We are building the matching system that powers this connection, from search and discovery to ranking and personalization. Our goal is to combine cutting-edge machine learning with a deep understanding of patient and provider experience.

About the role

We are looking for a Senior Machine Learning Engineer to be a core contributor to Headway's ranking and relevance systems. You will design, build, and ship ML models that determine how patients discover and connect with therapists — using search, recommendation, and personalization techniques to improve matching quality across the care journey.

In this role, you will work with significant autonomy on scoped problem areas, contribute to technical direction, and collaborate closely with product, engineering, and data science to drive measurable outcomes for patients and providers.

What you’ll do

At Headway, one of our most important challenges is ensuring that patients find the right therapist quickly and effectively. We are investing deeply in search, ranking, and relevance systems powered by machine learning. As a Senior Machine Learning Engineer, you will focus on:

• Matching and ranking: Build and iterate on ML models that power how patients discover and connect with providers — from candidate generation to final ranking.
• Personalization: Leverage patient signals, provider attributes, and outcomes data to improve matching accuracy and relevance over time.
• Model development end-to-end: Own the full lifecycle of models you build — from offline evaluation and experimentation to production deployment and monitoring.
• Experimentation: Design and analyze A/B tests, define the right offline proxies and online metrics, and translate results into product decisions.
• Cross-functional collaboration: Partner with product managers, software engineers, and data scientists to scope problems, align on success metrics, and ship improvements that move the needle for patients.
• Raising the bar: Contribute to ML best practices on the team — through code reviews, documentation, and sharing what you learn from the systems you build.

Who you are

• You have 5+ years of experience in applied ML roles, with at least 3 years of meaningful hands-on modeling work in ranking, relevance, recommendations, search, or personalization.
• You are fluent in Python and experienced with ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or CatBoost.
• You have taken ML models from prototype to production and understand what it takes to make them reliable, maintainable, and performant at scale.
• You are comfortable designing and running A/B experiments, selecting appropriate metrics, and interpreting results with rigor.
• You bring product intuition alongside technical depth — you care about making the patient experience meaningfully better, not just improving an offline metric.
• You work well in collaborative, cross-functional environments and can communicate technical tradeoffs clearly to non-ML stakeholders.

Nice to have

• Experience with search, discovery, matching systems or consumer facing personalization.
• Familiarity with modern retrieval techniques (vector search, embeddings, semantic search).
• Exposure to ML infrastructure such as feature stores, model monitoring, and retraining pipelines.
• Experience with Metaflow, SageMaker, and Outerbounds.
• Background in healthcare, marketplace, or other B2C domains where user-provider or user-product fit is the core product problem.

Our interview process

After you apply to Headway, here are some details of what to expect during the interview process.

1. Initial screen: You’ll connect with someone in recruiting so you can learn more about the team, Headway’s mission and exciting growth, and we can get a better idea of your background.
2. First round: You’ll meet with an engineer on the team to do some live coding and learn more about the engineering team.
3. Final rounds: You’ll meet several more team members for technical and non-technical interviews and leave with a fuller picture of what it’s like to work at Headway.
4. References and the offer: Our favorite part of the process. We’ll send over all of the details, including specifics on employee equity, and congratulatory messages from excited future team members.

Compensation and Benefits:

The expected base pay range for this position is $218,500 - $273,125, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for an equity grant, depending on the position and level.

We are committed to offering a comprehensive and competitive total rewards package, including robust health and wellness benefits, retirement savings, and meaningful ownership opportunities through equity. Compensation decisions are made holistically, ensuring fairness and alignment with market benchmarks while recognizing individual contributions and potential.

• Benefits offered include:
• Equity compensation
• Medical, Dental, and Vision coverage
• HSA / FSA
• 401K
• Work-from-Home Stipend
• Therapy Reimbursement
• 16-week parental leave for eligible employees
• Carrot Fertility annual reimbursement and membership
• 13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st
• Flexible PTO
• Employee Assistance Program (EAP)
• Training and professional development

Research Engineer, Multimodal Generative AI (Image/Video)

Seattle, WA

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

Snapshot

The role of the Research Engineer will be to develop state-of-the-art methods for multimodal generative AI models, with a primary focus on image generation and editing. This role is for the team behind “Nano Banana”.

At Google DeepMind, we've built a unique culture and work environment where long-term ambitious research can flourish. Our special interdisciplinary team combines the best techniques from deep learning, reinforcement learning, and systems neuroscience to build general-purpose learning algorithms. We have already made a number of high-profile breakthroughs towards building artificial general intelligence, and we have all the ingredients in place to make further significant progress over the coming year!

About Us

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

The Role

Research Engineers at Google DeepMind lead our efforts in developing novel tools, infrastructure, and algorithms towards the end goal of solving and building Artificial General Intelligence.

Having pioneered research in the world's leading academic and industrial labs, PhDs, post-docs, or professorships, Research Engineers join Google DeepMind to work collaboratively within and across Research fields. They are expected to independently build state of the art foundation models and research infrastructure, work with teams on large scale AI, and develop solutions to fundamental questions in machine learning and AI.

Drawing on expertise from a variety of disciplines including deep learning, computer vision, language modeling, and advanced generative architectures, our Research Engineers are at the forefront of groundbreaking research.

Key Responsibilities

• Design, rapidly implement, and rigorously evaluate cutting-edge deep learning algorithms, data curation, and evaluation infrastructure for multimodal generative AI, with a particular emphasis on image synthesis.
• Report and present research findings and developments clearly and efficiently both internally and externally, verbally and in writing.
• Suggest and engage in team collaborations to meet ambitious research goals, while also driving significant individual contributions.
• Work in collaboration with our Ethics and Governance teams to ensure our advances in intelligence are developed ethically and provide broad benefits to humanity.

About You

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

• PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience.
• Proven experience in deep learning research and development, particularly in generative AI and related to image synthesis. This includes diffusion models and autoregressive generative models. Experience with post-training is a plus. 
• Exceptional engineering skills in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch), with a track record of building high-quality research prototypes and systems.
• Strong publication record at top-tier machine learning, computer vision, and graphics conferences (e.g., NeurIPS, ICLR, ICML, SIGGRAPH, CVPR, ICCV).

In addition, the following would be an advantage: 

Demonstrated experience in multimodal generative modeling, especially combining large language models with visual generation (e.g., text-to-image/video systems, joint autoregressive and diffusion models).A keen eye for visual aesthetics and detail, coupled with a passion for creating high-quality, visually compelling generative content.

• A real passion for AI!

What We Offer

At Google DeepMind, we want employees and their families to live happier and healthier lives, both in and out of work, and our benefits reflect that. Some select benefits we offer: enhanced maternity, paternity, adoption, and shared parental leave, private medical and dental insurance for yourself and any dependents, and flexible working options. We strive to continually improve our working environment, and provide you with excellent facilities such as healthy food, an on-site gym, faith rooms, terraces etc.

We are also open to relocating candidates to Mountain View and offer a bespoke service and immigration support to make it as easy as possible (depending on eligibility).

The US base salary range for this full-time position is between $166,000 USD - $244,000 USD + bonus + equity + benefits. Your recruiter can share more about the specific salary range for your targeted location during the hiring process.

Note: In the event your application is successful and an offer of employment is made to you, any offer of employment will be conditional on the results of a background check, performed by a third party acting on our behalf. For more information on how we handle your data, please see our Applicant and Candidate Privacy Policy.

• Design, implement, and maintain ML deployment pipelines for scalable production systems.
• Operationalize large language models (LLMs) and other AI/ML models, ensuring high availability and reliability.
• Build robust model monitoring, logging, and alerting systems to track performance and detect drift.
• Partner with data scientists to transition models from research/prototype into production-ready deployments.
• Develop CI/CD pipelines for ML workflows, integrating testing, validation, and automated deployment.
• Optimize runtime performance of ML models across cloud platforms (AWS, GCP, Azure) and distributed systems.
• Apply containerization and orchestration (Docker, Kubernetes) to enable reproducible, scalable systems.
• Collaborate with cross-functional teams to ensure ML systems align with platform goals and business requirements.

• 5+ years of experience as a Machine Learning Engineer, MLOps Engineer, or similar role.
• Proven experience deploying and maintaining machine learning models in production at scale.
• Hands-on experience with ML lifecycle tooling (MLflow, Kubeflow, SageMaker, Vertex AI, or similar).
• Strong proficiency in Python; familiarity with ML frameworks such as PyTorch or TensorFlow.
• Deep knowledge of containerization (Docker) and orchestration (Kubernetes) for production ML systems.
• Expertise with cloud platforms (AWS, GCP, Azure) for ML deployment and scaling.
• Strong understanding of MLOps best practices, monitoring, and automation.
• Excellent problem-solving skills, with an emphasis on building reliable, scalable systems.
• Strong communication and collaboration skills across technical and non-technical teams.

• Leverage 5+ years of experience in data science to design, implement, and optimize machine learning models and pipelines.
• Develop, fine-tune, and evaluate large language models (LLMs) for a variety of applications, ensuring accuracy, performance, and robustness.
• Collaborate with engineering and product teams to integrate AI/ML solutions into our platform in a scalable and maintainable way.
• Conduct applied research, staying current on advances in LLMs, generative AI, and data science methodologies, and translate them into practical solutions.
• Build end-to-end workflows, from data exploration and feature engineering to training, validation, deployment, and monitoring in production.
• Apply modern containerization and orchestration techniques (e.g., Docker, Kubernetes) to support reproducible experimentation and deployment.
• Work with cloud platforms (e.g., Databricks, AWS, GCP, Azure) to manage data pipelines, large-scale training jobs, and distributed systems.
• Collaborate across teams to ensure our AI capabilities align with platform goals and business needs.

• 5+ years of experience as a Data Scientist or Machine Learning Engineer, with proven success in deploying models to production.
• Hands-on experience with large language models (LLMs); fine-tuning experience strongly preferred.
• Strong background in Python and ML frameworks such as PyTorch or TensorFlow.
• Proficiency in containerization and orchestration technologies (Docker, Kubernetes).
• Experience with cloud platforms and ML ecosystems (Databricks, AWS, GCP, Azure).
• Familiarity with MLOps best practices, including model deployment, monitoring, and CI/CD for ML.
• Strong analytical and problem-solving skills, with the ability to translate research into production-ready solutions.
• Excellent communication and collaboration skills, with the ability to work effectively across product, engineering, and leadership teams.
• A proactive, self-starter mindset with a passion for applied research and innovation.