Senior Lead Machine Learning Engineer Job at Capital One (San Jose)

Senior Machine Learning Systems Engineer

Our organization drives AI innovation across Jira products. We deliver seamless ...

Location

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Extensive experience building Machine Learning and AI solutions (4+ years)
Proven experience developing, deploying, and maintaining end-to-end ML systems, including data engineering, model serving, and monitoring
Expert proficiency with GenAI frameworks and tools, including developing and fine-tuning large language models (LLMs) and building retrieval-augmented generation (RAG) systems
Expert proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX
Experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models

Job Responsibility

Collaborate with software engineers, data scientists, and product managers to solve complex problems
Lead projects from technical design through launch
Partner with teams to achieve impactful results
Deliver robust ML solutions to build AI features reaching millions
This includes curating ML datasets, fine-tuning open-source LLMs, or accessing proprietary LLMs
Mentor junior members of the team

What we offer

Health and wellbeing resources
Paid volunteer days

Senior Machine Learning Engineering Manager, Gen AI

We're seeking a Senior Machine Learning Manager (M60) to lead a cross-functional...

Location

United States

Salary:

193500.00 - 303150.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

8+ years in ML, search, or backend engineering roles, with 3+ years leading teams
Strong track record of shipping ML-powered or LLM-integrated user-facing products
Experience with RAG systems (vector search, hybrid retrieval, LLM orchestration)
Deep experience in either modeling (e.g., LLMs, search, NLP) or engineering (e.g., backend infra, full-stack), with the ability to lead end-to-end
Deep understanding of LLM ecosystems (OpenAI, Claude, Mistral, OSS), orchestration frameworks (LangChain, LlamaIndex), and vector databases (Weaviate, Pinecone, FAISS, etc.)
Strong product intuition and ability to translate complex tech into valuable user features
Familiarity with GenAI evaluation methods: hallucination detection, groundedness scoring, and human-in-the-loop feedback loops
Master’s or PhD in Computer Science, Machine Learning, or related field preferred—or equivalent practical experience

Job Responsibility

Lead the vision, design, and execution of LLM-powered AI products, leveraging advance AI modeling (e.g. SLM post-training/fine-tuning), RAG architectures and hybrid ranking system
Define system architecture across retrievers, rankers, orchestration layers, prompt templates, and feedback mechanisms
Work closely with product and design teams to ensure delightful, fast, and grounded user experiences
Build and manage a cross-disciplinary team including ML engineers, backend/frontend engineers, and applied scientists
Foster a culture of E2E ownership — empowering the team to move from prototype to production quickly and iteratively
Mentor individuals to grow in both technical depth and product acumen
Shape the technical roadmap and long-term strategy for GenAI search across Atlassian’s product suite
Partner with platform and infra teams to scale inference, evaluate performance, and integrate usage signals for continuous improvement
Champion data quality, grounding, and responsible AI practices in all deployed features

What we offer

health and wellbeing resources
paid volunteer days

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 Machine Learning Engineer (Infrastructure)

We are looking for an experienced MLOps Engineer to join our team as a Senior Ma...

Location

United States , Boston

Salary:

152800.00 - 224100.00 USD / Year

SimpliSafe

Expiration Date

Until further notice

Requirements

5+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure
Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks
Hands-on experience with: CI/CD pipelines, Docker
Kubernetes
Infrastructure-as-code tools (e.g., Terraform, Cloud Formation)
Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch)
Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring
LLM application development, including prompt engineering and evaluation
Strong communication skills for partnering with cross-functional technical and non-technical teams

Job Responsibility

Lead the architecture, deployment, and optimization of scalable ML model serving systems for real-time and batch use cases
Collaborate with data scientists, engineers, and stakeholders to operationalize ML models
Develop CI/CD pipelines for ML models enabling rapid, safe, and consistent model releases
Design, implement, and own comprehensive production monitoring for ML models/systems
Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads
Drive best practices in model versioning, observability, reproducibility, and deployment reliability
Serve in an on-call rotation as a first responder for software owned by your team

What we offer

A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive
A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families
Free SimpliSafe system and professional monitoring for your home
Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change
Participation in our annual bonus program, equity, and other forms of compensation
A full range of medical, retirement, and lifestyle benefits

Fulltime

LLM - Senior Staff Engineer - Python + Machine Learning

AquSag is seeking a hands-on Machine Learning Senior Staff Engineer to lead cros...

Location

Salary:

40.00 - 60.00 USD / Hour

AquSag Technologies

Expiration Date

Until further notice

Requirements

9+ yrs of strong background in Machine Learning, NLP, and modern deep learning architectures (Transformers, LLMs)
Hands-on experience with frameworks such as PyTorch, TensorFlow, Hugging Face, or DeepSpeed
Hands-on experience in Docker for Production deployment
Proven experience managing teams delivering ML/LLM models in production environments
Knowledge of distributed training, GPU/TPU optimization, and cloud platforms (AWS, GCP, Azure)
Familiarity with MLOps tools like MLflow, Kubeflow, or Vertex AI for scalable ML pipelines
Excellent leadership, communication, and cross-functional collaboration skills
Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD preferred)
Overlap of 6 hours with PST time zone is mandatory
Commitments Required: 8 hours per day with overlap of 6 hours with PST

Job Responsibility

Lead and mentor a cross-functional team of ML engineers, data scientists, and MLOps professionals
Oversee the full lifecycle of LLM and ML projects — from data collection to training, evaluation, and deployment
Collaborate with Research, Product, and Infrastructure teams to define goals, milestones, and success metrics
Provide technical direction on large-scale model training, fine-tuning, and distributed systems design
Implement best practices in MLOps, model governance, experiment tracking, and CI/CD for ML
Manage compute resources, budgets, and ensure compliance with data security and responsible AI standards
Communicate progress, risks, and results to stakeholders and executives effectively

Fulltime

Senior Staff Machine Learning Engineer

Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pi...

Location

United States

Salary:

232000.00 - 310000.00 USD / Year

Affirm

Expiration Date

Until further notice

Requirements

10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems
Experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment
Proficient in Python and ML frameworks, including PyTorch and XGBoost
Strong understanding of representation learning and embedding-based modeling
Deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems
Deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining
Strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams
Exceptional judgment, collaboration, and communication skills
Strong verbal and written communication skills that support effective collaboration across our global engineering organization
Equivalent practical experience or a Bachelor’s degree in a related field

Job Responsibility

Define and drive multi-year, multi-team technical strategy for machine learning across Affirm
Lead the design, implementation, and scaling of advanced ML systems
Partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities
Provide broad technical leadership across the ML organization, mentoring senior engineers
Drive clarity and alignment on ambiguous, high-stakes technical decisions
Champion operational and system excellence at the area level

What we offer

Equity rewards
Monthly stipends for health, wellness and tech spending
100% subsidized medical coverage, dental and vision for you and your dependents
Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
Competitive vacation and holiday schedules
Employee stock purchase plan enabling you to buy shares of Affirm at a discount

Fulltime

Senior Staff Machine Learning Engineer

Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pi...

Location

Canada

Salary:

206000.00 - 256000.00 CAD / Year

Affirm

Expiration Date

Until further notice

Requirements

10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems
Experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment
Proficiency in Python and ML frameworks, including PyTorch and XGBoost
Experience with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent
Strong understanding of representation learning and embedding-based modeling
Deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems
Deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining
Strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams
Exceptional judgment, collaboration, and communication skills
Strong verbal and written communication skills

Job Responsibility

Define and drive multi-year, multi-team technical strategy for machine learning across Affirm
Lead the design, implementation, and scaling of advanced ML systems
Partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities
Provide broad technical leadership across the ML organization
Drive clarity and alignment on ambiguous, high-stakes technical decisions
Champion operational and system excellence at the area level

What we offer

Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
Time off - competitive vacation and holiday schedules
ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

Fulltime

Senior Machine Learning Engineer

Start.io, a leading mobile marketing and audience platform, empowers the app eco...

Location

Salary:

Not provided

Start.io

Expiration Date

Until further notice

Requirements

B.Sc. or M.Sc. in Computer Science, Software Engineering, or a related technical discipline
5+ years of experience building high-performance backend or ML inference systems
Deep expertise in Python and experience with low-latency APIs and real-time serving frameworks (e.g., FastAPI, Triton Inference Server, TorchServe, BentoML)
Experience with scalable service architecture, message queues (Kafka, Pub/Sub), and async processing
Strong understanding of model deployment practices, online/offline feature parity, and real-time monitoring
Experience in cloud environments (AWS, GCP, or OCI) and container orchestration (Kubernetes)
Experience working with in-memory and NoSQL databases (e.g. Aerospike, Redis, Bigtable) to support ultra-fast data access in production-grade ML services
Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry) and best practices for alerting and diagnostics
A strong sense of ownership and the ability to drive solutions end-to-end
Passion for performance, clean architecture, and impactful systems

Job Responsibility

Own and lead the design and development of low-latency Algo inference services handling billions of requests per day
Build and scale robust real-time decision-making engines, integrating ML models with business logic under strict SLAs
Collaborate closely with DS to deploy models seamlessly and reliably in production
Design systems for model versioning, shadowing, and A/B testing at runtime
Ensure high availability, scalability, and observability of production systems
Continuously optimize latency, throughput, and cost-efficiency using modern tooling and techniques
Work independently while interfacing with cross-functional stakeholders from Algo, Infra, Product, Engineering, BA & Business

What we offer

Lead the mission-critical inference engine that drives our core product
Join a high-caliber Algo group solving real-time, large-scale, high-stakes problems
Work on systems where every millisecond matters, and every decision drives real value
Enjoy a fast-paced, collaborative, and empowered culture with full ownership of your domain

Senior Lead Machine Learning Engineer

Capital One

Location:
United States , San Jose ▼
New York
San Francisco
McLean

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
January 06, 2026

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Capital One

Location:United States , San Jose ▼New YorkSan FranciscoMcLean

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Job Posted:January 06, 2026

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