Senior Machine Learning Engineer, Safety Job at Patreon

Senior Machine Learning Engineer, Agentic

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Bellevue; Menlo Park; New York; Washington; Denver; Westlake; Chicago; Lake Mary; Clearwater; Gainesville

Salary:

146000.00 - 220000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

Strong technical expertise in software development, with understanding of agentic workflows—including reasoning loops, tool invocation, memory, and orchestration of autonomous AI agents
Hands-on experience using Large Language Models, including prompt engineering, fine-tuning, model distillation, and deploying optimized models (e.g. via DPO, PPO) into production environments
Proven ability to build and scale ML/AI systems, from experimentation to deployment—owning dataset generation, evaluation pipelines, A/B testing, and performance monitoring
Leadership and mentorship capabilities, with a track record of guiding complex technical projects and supporting the growth of teammates through code/design reviews and technical direction
Excellent communication and collaboration skills, with the ability to translate technical ideas into actionable plans and work effectively with cross-functional partners, including product and infrastructure teams
Innovation mindset and commitment to continuous learning and a bias toward action, staying at the forefront of ML/AI trends, agentic systems research, and best practices in tooling, safety, and evaluation

Job Responsibility

Design and create tools and workflows for agent development that support rapid prototyping—define agents, compose toolchains, and construct reasoning loops with minimal overhead
Build platform solutions to support scalable experimentation, synthetic dataset generation, and multi-agent evaluation across diverse tasks and domains
Develop feedback and optimization pipelines that incorporate both automated metrics and human-in-the-loop evaluation signals to fine-tune agent behavior
Implement and scale optimization techniques such as Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), and reward modeling to improve agent performance
Launch and support fine-tuned models in production environments with robust evaluation, rollback strategies, and performance monitoring
Collaborate closely with applied AI/ML teams to translate state-of-the-art research in agentic reasoning, planning, and tool use into reliable, production-ready systems

What we offer

Market competitive and pay equity-focused compensation structure
100% paid health insurance for employees with 90% coverage for dependents
Annual lifestyle wallet for personal wellness, learning and development, and more
Lifetime maximum benefit for family forming and fertility benefits
Dedicated mental health support for employees and eligible dependents
Generous time away including company holidays, paid time off, sick time, parental leave, and more
Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits
Bonus opportunities
Equity

Fulltime

Senior Principal Machine Learning Engineer

You’ll form a new team of passionate engineers dedicated to building and scaling...

Location

United States

Salary:

222300.00 - 348975.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Mathematics, or a related field, or equivalent practical experience
12+ years of industry experience in machine learning, data science, or AI, with a proven track record of delivering production-grade ML systems
Deep expertise in Python, Go, or Java, with the ability to write performant, production-quality code
familiarity with SQL, Spark, and cloud data environments (e.g., AWS, GCP, Databricks)
Experience building and scaling ML models for business-critical applications, ideally in security, privacy, anti-abuse, or compliance domains
Strong communication skills, able to explain complex ML concepts to diverse audiences and influence stakeholders
Demonstrated ability to solve ambiguous, complex problems and drive projects from ideation to production
Agile development mindset, with a focus on iterative improvement and business impact

Job Responsibility

Lead AI/ML Strategy for Trust: Drive the development and implementation of advanced machine learning algorithms and AI systems for Trust, Security, Product Abuse, and Compliance use cases (e.g., threat detection, vulnerability management, privacy automation, AI safety)
Architect and Scale ML Platforms: Design and build scalable, secure, and reliable ML infrastructure and pipelines, ensuring compliance with privacy and regulatory requirements
AI Safety and Responsible AI: Develop and champion AI safety practices, including output moderation, explainability, and alignment with evolving regulatory frameworks
Cross-Functional Collaboration: Partner with product, engineering, security, privacy, and analytics teams to deliver transformative AI/ML solutions that enhance Atlassian’s trust posture
Mentorship and Leadership: Mentor and guide ML engineers and data scientists, fostering a culture of technical excellence, innovation, and continuous improvement
Innovation and Research: Stay at the forefront of AI/ML research, evaluating and applying the latest techniques (e.g., LLMs, anomaly detection, privacy-preserving ML) to real-world Trust challenges
Platform Enablement: Build reusable ML services and APIs that empower other teams to integrate AI/ML into their products and workflows
Operational Excellence: Ensure high availability, reliability, and security of all ML-powered Trust platforms and services

What we offer

health and wellbeing resources
paid volunteer days
benefits, bonuses, commissions, and equity

Fulltime

Senior Data Scientist, Rides Safety

You'll own Bolt's Safety automation and prediction systems end-to-end and direct...

Location

Estonia , Tallinn; Tartu

Salary:

Not provided

Bolt

Expiration Date

Until further notice

Requirements

Strong ownership mindset and comfort working autonomously from problem research to model deployment
3+ years of experience in machine learning for automated decision making
Exceptional knowledge of machine learning algorithms, statistical inference, and autonomous decision-making systems
Mastery in Python and SQL
Skilled at communication with cross-functional stakeholders

Job Responsibility

Identify, research, and prioritise hypotheses to improve automated and predictive safety algorithms (e.g., risk scoring, verification, and progressive interruption systems)
Develop, deploy, and monitor automated safety systems, ranging from classical supervised learning to real-time risk models and advanced control system designs
Design and run large-scale experiments to validate safety approaches and estimate their impact on core safety metrics (e.g., incident rates, verification success, and driver/rider experience)
Lead the data science and ML-first approach to safety and risk management in the company
Partner with analysts, engineers, product managers, and operations specialists to identify safety problems and develop the most efficient, data-informed solutions

What we offer

relocation and visa support

Senior Platform Manager, Trust and Safety

As a Product Manager in the Trust & Safety team, you will identify customer pain...

Location

United States

Salary:

177000.00 - 208000.00 USD / Year

Airbnb

Expiration Date

Until further notice

Requirements

5+ years product management experience
Prior product, operation, or engineering experience in security, trust, safety, risk or fraud
Outstanding written and verbal communication ability to a diverse stakeholder audience, including a global team of C-level executives, product, and technical stakeholders
Strong analytical, troubleshooting, and problem-solving skills
Experience building machine learning products or technical product management
Experienced in design, and hypothesis driven product development
Entrepreneurial drive to achieve stretch goals in an innovative fast-paced environment
Exceptional collaboration, partnership and influencing skills with the ability to work in a global environment across multiple locations and time zones to drive consensus across teams
Experience leading teams through ambiguity, and high stakes trade off decisions

Job Responsibility

Creating vision and strategy for Trust & Safety products and platforms
Leading a cross-functional working group of engineers, data scientists, designers, operations experts, and policy experts to ensure alignment, execution, and launches
Maintaining product backlog and the product roadmap. Own prioritization process of product solutions based on business value and customer impact
Defining goals and success with clearly measurable objectives and key results
Building alignment across product teams (inside and outside of Trust & Safety), and Leadership/Executive teams
Anticipating bottlenecks, making tradeoffs and balancing the business needs, customer needs, versus technical or operational constraints
Presenting product roadmap and status to the business and Airbnb leadership on an ongoing basis. Communicate concisely and influence outcomes
Evaluating new product opportunities and bring forward proposals (buy, build, partner solutions) for new capabilities with data and users at the forefront
Developing short term plans aligned with long term goals to iteratively build platform capabilities to defend against fraud, abuse, safety, unwanted bad activities, etc
Becoming the thought leader and entrepreneur that others within Airbnb look up to for knowledge, processes, and methods on building products and platforms

What we offer

bonus
equity
benefits
Employee Travel Credits

Fulltime

Principal Engineer

The Principal AI/ML Operations Engineer leads the architecture, automation, and ...

Location

United States , Pleasanton, California

Salary:

251000.00 - 314500.00 USD / Year

BlackLine

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field
10+ years in ML infrastructure, DevOps, and software system architecture
4+ years in leading MLOps or AI Ops platforms
Strong programming skills in languages such as Python, Java, or Scala
Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow)
Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure)
Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management
Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation
Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking
Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads

Job Responsibility

Define enterprise-level standards and reference architectures for ML-Ops and AIOps systems
Partner with data science, security, and product teams to set evaluation and governance standards (Guardrails, Bias, Drift, Latency SLAs)
Mentor senior engineers and drive design reviews for ML pipelines, model registries, and agentic runtime environments
Lead incident response and reliability strategies for ML/AI systems
Lead the deployment of AI models and systems in various environments
Collaborate with development teams to integrate AI solutions into existing workflows and applications
Ensure seamless integration with different platforms and technologies
Define and manage MCP Registry for agentic component onboarding, lifecycle versioning, and dependency governance
Build CI/CD pipelines automating LLM agent deployment, policy validation, and prompt evaluation of workflows
Develop and operationalize experimentation frameworks for agent evaluations, scenario regression, and performance analytics

What we offer

short-term and long-term incentive programs
robust offering of benefit and wellness plans

Fulltime

Director of AI Engineering

We are entering a hyper-growth phase of AI innovation and are hiring a Director ...

Location

Canada; United States

Salary:

300000.00 - 450000.00 USD / Year

Apollo.io

Expiration Date

Until further notice

Requirements

10–15+ years in software engineering, with significant leadership experience owning AI/ML or applied LLM systems at scale
Proven history shipping LLM-powered features, agentic workflows, or AI assistants used by real customers in production
Deep understanding of LLM orchestration frameworks (LangChain, LlamaIndex), RAG pipelines, vector search, embeddings, and prompt engineering
Expert in backend & distributed systems (Python strongly preferred) and cloud infrastructure (AWS/GCP)
Strong experience with telemetry, observability, and cost-aware real-time inference optimizations
Demonstrated ability to lead senior engineers, define technical roadmaps, and deliver outcomes aligned to business metrics
Experience building or scaling teams working on experimentation, optimization, personalization, or ML-powered growth systems
Exceptional ability to simplify complex problems, set clear standards, and drive alignment across Product, Data, Design, and Engineering
Strong product sense, ability to weigh novelty vs. impact, focus on user value, and prioritize speed with guardrails
Fluent in integrating AI tools into engineering workflows for code generation, debugging, delivery velocity, and operational efficiency

Job Responsibility

Define the multi-year technical vision for Apollo’s AI stack, spanning agents, orchestration, inference, retrieval, and platformization
Prioritize high-impact AI investments by partnering with Product, Design, Research, and Data leaders to align engineering outcomes with business goals
Establish technical standards, evaluation criteria, and success metrics for every AI-powered feature shipped
Lead the architecture and deployment of long-horizon autonomous agents, multi-agent workflows, and API-driven orchestration frameworks
Build reusable, scalable agentic components that power GTM workflows like research, enrichment, sequencing, lead scoring, routing, and personalization
Own the evolution of Apollo’s internal LLM platform for high-scale, low-latency, cost-optimized inference
Oversee model-driven experiences for natural-language interfaces, RAG pipelines, semantic search, personalized recommendations, and email intelligence
Partner with Product & Design to build intuitive conversational UX that hides underlying complexity while elevating user productivity
Implement rigorous evaluation frameworks, including offline benchmarking, human-in-the-loop review, and online A/B experimentation
Ensure robust observability, monitoring, and safety guardrails for all AI systems in production

What we offer

Equity
Company bonus or sales commissions/bonuses
401(k) plan
At least 10 paid holidays per year
Flex PTO
Parental leave
Employee assistance program and wellbeing benefits
Global travel coverage
Life/AD&D/STD/LTD insurance
FSA/HSA

Fulltime

Senior Robotics Software Engineer, Test

As a Senior Robotics Software Engineer, Test at Chef Robotics, you'll develop co...

Location

United States , San Francisco

Salary:

150000.00 - 240000.00 USD / Year

Chef Robotics

Expiration Date

Until further notice

Requirements

Bachelor's degree in Robotics, Computer Science, Computer Vision, Mechanical Engineering, or related technical field
7+ years of professional experience in robotics software development, perception systems, or testing
Expert-level programming skills in Python with advanced software engineering capabilities
Extensive experience with robotics simulation environments (Gazebo, PyBullet, MuJoCo, or similar)
Strong background in computer vision and perception system development and testing
Deep familiarity with robot control systems, motion planning, and real-time robotics software
Proven experience with CI/CD pipeline development and test automation frameworks
Advanced understanding of test automation principles, methodologies, and best practices
Deep understanding of robotics kinematics, dynamics, and control systems with practical testing experience
Extensive experience with computer vision algorithms, image processing, and perception pipeline testing

Job Responsibility

Robotics Test Framework Development
Design and implement automated testing frameworks for robot motion planning and control systems
Develop advanced evaluation frameworks for core robot behaviors over hundreds of scenarios
Develop advanced validation frameworks for real-time control loop performance and stability across diverse operational conditions
Build sophisticated test harnesses for hardware-software integration validation
Architect simulation environments for testing robotic behavior without physical hardware dependencies
Perception System Testing & Validation
Design and implement comprehensive testing frameworks for computer vision algorithms and perception pipelines
Create automated test suites for object detection, segmentation, and classification in food production environments
Develop validation systems for camera calibration and depth estimation accuracy

What we offer

medical, dental, and vision insurance
commuter benefits
flexible paid time off (PTO)
catered lunch
401(k) matching
early-stage equity

Fulltime

Associate Director, Reinforcement Learning (ML)

Lead Amgen’s strategy and execution for Reinforcement Learning from Human Feedba...

Location

United States , Thousand Oaks; Jacksonville

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Doctorate degree and 3 years of Computer Science, IT or related field experience
Master’s degree and 5 years of Computer Science, IT or related field experience
Bachelor’s degree and 7 years of Computer Science, IT or related field experience
Associate’s degree and 12 years of Computer Science, IT or related field experience
High school diploma / GED and 14 years of Computer Science, IT or related field experience
Deep, hands-on expertise in Reinforcement Learning from Human Feedback (RLHF) and/or advanced reinforcement learning, including reward modeling, policy optimization, exploration strategies, and offline/online evaluation
Demonstrated experience deploying RLHF or RL systems into production for real-world applications (e.g., large language models, recommendation systems, decision support tools, or workflow automation), ideally in healthcare, life sciences, or other regulated domains
Strong background in modern machine learning and deep learning, with practical experience in Python and frameworks such as PyTorch or TensorFlow, and familiarity with LLM ecosystems and tooling
Experience driving sophisticated, cross-functional initiatives, collaborating with non-technical stakeholders (e.g., physicians, scientists, commercial leaders, compliance, legal) and translating needs into impactful AI solutions
Strong ability to communicate complex technical topics simply, tailoring content to senior executives and non-technical audiences

Job Responsibility

Lead the design and development of RLHF systems including reward modeling, policy optimization, safety and alignment mechanisms, and evaluation frameworks for large language models and other AI systems
Drive hands-on technical execution, particularly for high-impact projects, reviewing architectures, experimentation plans, and code, and helping the team navigate scientific and engineering trade-offs
Establish best-practice pipelines for human feedback, partnering closely with internal customer teams to define feedback protocols, annotation quality standards, and governance for RLHF data
Define and track success metrics for RLHF systems, balancing offline and online evaluation, A/B tests, safety and robustness criteria, and business or scientific outcomes
Collaborate across Amgen leaders to ensure RLHF solutions are aligned with strategy, compliant with policy, and integrated into real workflows
Partner with Data, Platform and Technology teams to ensure that RLHF workloads are supported by scalable data platforms, model hosting, experimentation infrastructure, and MLOps best practices
Champion responsible and compliant AI, working with Legal, Compliance, and Information Security to implement governance around human feedback, data usage, model behavior, transparency, and risk management in a regulated environment
Communicate insights and influence senior stakeholders, creating clear narratives, roadmaps, and recommendations that help executives understand RLHF trade-offs, risks, and opportunities

What we offer

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible

Senior Machine Learning Engineer, Safety

Patreon

Location:
United States

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
February 21, 2026

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