Senior Machine Learning Engineer, Safety Job at Patreon

Senior Machine Learning Engineer (Team Lead)

As our Artificial Intelligence (AI) and Machine Learning (ML) Team Leader, you w...

Location

Australia , South Bank

Salary:

Not provided

Flight Centre Brand

Expiration Date

Until further notice

Requirements

7+ years delivering production grade ML or AI systems with proven commercial impact
3+ years Leading and Mentoring engineers
Experience building AI agents, RAG systems or LLM powered applications in production
Demonstrated experience leading technical teams and managing complex AI programmes
Strong hands on experience across ML infrastructure, distributed systems and scalable AI architecture
Experience building and governing AI agent platforms including endpoints, gateways and tool orchestration
Familiarity with MCP servers and emerging agent communication standards and protocols
Experience defining evaluation frameworks, safety mechanisms and governance for LLM and agent based systems
Deep knowledge of Python, modern AI/ML frameworks and scalable AI platforms including Databricks
Strong expertise in Kubernetes and cloud native production environments

Job Responsibility

Lead the development and productionisation of ML models, LLM powered systems and agent based applications
Define and build end to end MLOps including CI CD, model registry, monitoring, drift detection and retraining for predictive ML systems
Establish LLMOps standards including context engineering, automated evaluation pipelines, red teaming, safeguards and policy guardrails
Architect and build AI agent workflows, endpoints, gateways and orchestration layers enabling secure tool access, structured reasoning and multi agent collaboration
Design and govern MCP servers and modern agent communication protocols to ensure interoperability, security and scalability
Implement strong observability across ML and GenAI systems including reliability, latency, evaluation metrics, usage tracking and cost control
Drive scalable ML infrastructure, feature stores and data platforms on Databricks
Oversee Kubernetes based deployments and cloud native AI infrastructure
Partner with senior stakeholders to prioritise and deliver multiple high impact AI initiatives
Coach and grow a high performing AI engineering team

What we offer

Individualised, ongoing Learning & Development via communities of practice
Innovation Days
Dedicated Engineering Days
Access to 'LinkedIn Learning' for ongoing skills development
Women in PM&E group
Exclusive Staff Discounts
Travel Discounts
Career opportunities in a network of brands and businesses across the globe
Corporate Health Discounts
Mental Health Support and Employee Assistance Program for staff and family

Fulltime

Senior Machine Learning Engineer

As our Senior ML Engineer, you will play a key role in delivering high impact, f...

Location

Australia , South Bank

Salary:

Not provided

Flight Centre Brand

Expiration Date

Until further notice

Requirements

5+ years delivering production grade ML or AI systems with commercial impact
Strong hands on experience across AI/ML lifecycle, infrastructure and scalable AI architecture
Experience building AI agents, RAG systems or LLM powered applications in production
Familiarity with agent endpoints, gateways and tool orchestration patterns
Exposure to MCP servers and emerging agent protocols
Experience implementing evaluation frameworks and safety mechanisms for LLM systems
Deep knowledge of Python and modern AI/ML frameworks
Experience working with Databricks
Strong understanding of Kubernetes and distributed production systems

Job Responsibility

Design, develop and productionise ML models, LLM powered systems and agent based applications
Implement end to end MLOps pipelines including CI CD, model registry, monitoring, drift detection and retraining for predictive ML systems
Build LLMOps workflows including context engineering, automated evaluation, safeguards and guardrails
Develop AI agent workflows, endpoints, gateways and orchestration layers enabling secure tool usage and structured reasoning
Contribute to MCP server implementation and modern agent communication protocols
Implement strong observability across ML and GenAI systems including reliability, latency, evaluation metrics, usage and cost tracking
Build scalable ML infrastructure, and AI/ML optimised workflows
Deploy and optimise workloads on Kubernetes and cloud native environments
Collaborate with product and business stakeholders to deliver high impact AI solutions

What we offer

Individualised, ongoing Learning & Development via communities of practice
Innovation Days
Dedicated Engineering Days
Access to 'LinkedIn Learning' for ongoing skills development
Women in PM&E group
Exclusive Staff Discounts
Travel Discounts
Career opportunities in a network of brands and businesses across the globe
Corporate Health Discounts
Mental Health Support and Employee Assistance Program for staff and family

Fulltime

Senior Machine Learning Engineer – Perception & Embodied AI

At General Motors, our product teams are redefining mobility. Through a human-ce...

Location

United States , Mountain View

Salary:

170600.00 - 261300.00 USD / Year

General Motors

Expiration Date

Until further notice

Requirements

BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related quantitative field
5+ years of professional experience with a focus on Computer Vision, Deep Learning, and Perception in a production environment
Deep hands-on experience with modern deep learning frameworks (e.g., PyTorch or TensorFlow) for training, experimentation, and debugging complex DNNs
Proven experience working with and fusing data from multiple sensor modalities (Camera, LiDAR, and/or Radar)
Practical experience deploying and optimizing ML models for resource-constrained, real-time embedded systems
Demonstrated ability to drive model improvements through large-scale data analysis, error logging, and data curation

Job Responsibility

End-to-End Model Lifecycle: Own the design, training, validation, and deployment of deep learning models for core perception tasks such as: 3D Object Detection and Tracking (vehicles, pedestrians, cyclists)
Real-time map detection of the drivable world (lanes, road boundaries, traffic signs)
Multi-Modal Sensor Fusion (Camera, LiDAR, Radar)
Production Pipeline: Build and scale the ML training infrastructure, including data mining and loading, multi-stage training and evaluation, to streamline model development
Performance Optimization: Improve model performance through data iterations, parameter tunings, training strategy and architecture updates to produce reliable models that meet and the strict real-time, low-latency requirements on the vehicle's embedded hardware
Model Debugging: Conduct rigorous, data-driven analysis to identify, debug, and resolve performance degradations and failures, specifically targeting long-tail and adversarial scenarios (e.g., adverse weather, sensor noise, occlusions)
Metric Definition: Define and implement robust model-level metrics to aid model development
System Integration: Work closely with the Safety, Systems, and other engineering functions to integrate Perception outputs

What we offer

medical
dental
vision
Health Savings Account
Flexible Spending Accounts
retirement savings plan
sickness and accident benefits
life insurance
paid vacation & holidays
tuition assistance programs

Fulltime

Senior Machine Learning Engineer

Patreon is looking for a Senior Machine Learning Engineer to support our mission...

Location

United States , San Francisco; New York

Salary:

200000.00 - 300000.00 USD / Year

Patreon

Expiration Date

Until further notice

Requirements

Minimum of 5 years of experience working in an end-to-end machine learning team environment: analyzing data, building and iterating on machine learning models, writing production-level code and shipping to production, monitoring performance, and A/B testing
Write clean and robust code in Python or other programming languages and have a keen eye for detail in code reviews
Experience debugging complex systems with a systematic approach
Curious mindset and dive deeply into datasets to understand our product and customers
Solid communication skills and write clear documentation
Growth mindset and aspire to continuously improve your soft and technical skills
Energized about building the first version of systems and are passionate about empowering creators with new machine learning solutions
Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or the equivalent

Job Responsibility

Conduct exploratory data analyses and proof-of-concept machine learning models to understand opportunities and potential project impact
Collaborate with cross-functional partners, such as product, engineering, design, legal, and trust and safety to design effective machine learning solutions
Analyze and prepare training data, including using crowdsourcing data labeling techniques
Train and iterate on machine learning models using novel techniques
Deploy machine learning models to production and write backend code when necessary to properly deploy the model
Debug models when observability shows performance gaps, and iterate on models

What we offer

Equity plans
Healthcare
Flexible time off
Company holidays and recharge days
Commuter benefits
Lifestyle stipends
Learning and development stipends
Patronage
Parental leave
401k plan with matching

Fulltime

Senior Machine Learning Engineer

Microsoft Purview is redefining how data protection works in an AI-native world....

Location

India , Hyderabad

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

8+ years of experience building and deploying machine learning systems in production environments
Strong hands-on experience with LLMs, RAG architectures, and applied Generative AI systems, including prompt design and grounding techniques
Proven expertise in designing end-to-end ML pipelines (data ingestion → feature engineering → training → evaluation → serving)
Experience defining and operationalizing offline and online evaluation frameworks (precision/recall, calibration, drift detection, A/B testing) and implementing guardrails for reliability and safety
Strong programming skills in Python, with experience in modern ML frameworks (e.g., PyTorch/TensorFlow) and cloud-based ML infrastructure
experience building multi-tenant SaaS AI systems with attention to scalability, latency, and cost optimization
Experience fine-tuning or adapting foundation models (e.g., LoRA/PEFT) and building agentic orchestration systems is preferred
knowledge of data security, compliance, or risk-scoring domains will be an additional advantage

Job Responsibility

Architect and productionize AI systems that power risk scoring, classifier-level reasoning, explainability narratives, and intelligent recommendations across multi-tenant SaaS environments
Design and build GenAI pipelines (RAG + agentic orchestration) including indexing, embedding strategies, retrieval optimization, prompt frameworks, tool integration, and memory/control flows tailored for security use cases
Own model evaluation and guardrails, defining offline/online metrics (precision, recall, risk calibration, hallucination control), building evaluation harnesses, and implementing responsible AI safeguards
Optimize model trade-offs (latency, cost, accuracy, safety) and deploy scalable inference systems with monitoring, drift detection, and feedback loops from customer signals
Partner with Product and Engineering to translate ambiguous security requirements into reliable AI-native workflows that are simple, trustworthy, and adoption-ready for SMB/SMC and Enterprise customers

Fulltime

Senior Machine Learning Engineer - Model Evaluations

The Public Sector ML team at Scale deploys advanced AI systems—including LLMs, a...

Location

United States , San Francisco; St. Louis; New York; Washington

Salary:

216300.00 - 300300.00 USD / Year

Scale

Expiration Date

Until further notice

Requirements

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

Job Responsibility

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

What we offer

Comprehensive health, dental and vision coverage
retirement benefits
a learning and development stipend
generous PTO

Fulltime

Senior Machine Learning Engineer

We are seeking a Senior Machine Learning Engineer to tackle some of the hardest ...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
4+ years of hands‑on experience building and shipping machine learning systems in production.
Solid foundation in ML fundamentals, including classification, anomaly detection, representation learning, and model evaluation.
Proficiency in Python and experience with modern ML frameworks (e.g., PyTorch, JAX, TensorFlow).
Experience designing end‑to‑end ML pipelines: data collection, training, evaluation, deployment, and monitoring.
Ability to reason about adversarial behavior, threat models, and failure modes in AI/ML systems.
Experience working on AI safety, trust, or security‑adjacent ML problems, including prompt injection, abuse detection, or adversarial ML.
Familiarity with agentic or LLM‑based systems, including tool calling, multi‑step reasoning, or orchestration flows.
Experience building ML evaluation and observability systems for real‑world AI behavior (e.g., adversarial testing, red‑team loops, robustness metrics).
Exposure to distributed ML systems, large‑scale data processing, or model serving in cloud environments.

Job Responsibility

Design, train, and deploy ML‑based defenses for threats such as prompt injection, adversarial inputs, and abuse of agentic workflows.
Develop adaptive detection and policy models that learn from evolving attacker behavior rather than relying solely on static rules or signatures.
Build and own evaluation frameworks for AI security, including adversarial testing, red‑teaming support, and continuous robustness measurement across real Copilot scenarios.
Partner with security and engineering teams to integrate ML defenses into secure orchestration frameworks that govern agent delegation, tool calling, and action execution.
Apply ML to encode security “common sense” and judgment into AI responses, balancing usefulness, safety, and user intent.
Monitor and analyze telemetry to improve model performance, reduce false positives/negatives, and guide iterative defense improvements.
Collaborate cross‑functionally with product, privacy, and AI platform teams to land agentic security patterns across Copilot and MAI.
Document and share applied ML security techniques, helping establish best practices for secure agentic AI across Microsoft.

Fulltime

Senior Machine Learning Engineer, Agentic

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

Location

United States , Menlo Park, CA; Bellevue, WA

Salary:

209000.00 - 245000.00 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
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

Translate product goals into measurable metrics and SLOs, and build a rigorous evaluation harness to continuously score agents performance
Develop feedback and optimization pipelines that uses both automated metrics and human-in-the-loop evaluation signals to improve agent behavior over time
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

Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
100% paid health insurance for employees with 90% coverage for dependents
Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
Employer-paid life & disability insurance, fertility benefits, and mental health benefits
Time off to recharge including company holidays, paid time off, sick time, parental leave, and more
Exceptional office experience with catered meals, events, and comfortable workspaces

Fulltime

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Senior Machine Learning Engineer, Safety

Job Description

Job Responsibility

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