Machine Learning Engineering

Machine Learning Engineering Jobs

7 jobs found

Today

AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)

Capital One San Jose, CA

San Jose, CA

Today

$215k - $246k/yr Full time Agentic Ai Ai Agent Ai Engineer

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Job Description

Build foundational AI systems that power real-world experiences for associates and customers. Capital One is hiring an AI Engineer 4 on the Intelligent Foundations and Experiences (IFX) team to design, deploy, and improve production AI capabilities including LLM inference and agentic AI. The role emphasizes end-to-end architecture, reliability, and optimization across scalability, cost, latency, and throughput.

What you’ll do

Partner with engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how associates work and how customers interact with Capital One.
Design, develop, test, deploy, and support AI software components, including foundation model training, LLM inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Apply and integrate a broad stack of Open Source and SaaS AI technologies, including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
Introduce state-of-the-art foundation model optimization techniques to improve production performance, including scalability, cost, latency, and throughput.
Contribute to technical vision and the long-term roadmap for foundational AI systems across Capital One.
Own end-to-end architecture for complex AI systems with an emphasis on maintainability, observability, and ethical alignment.
Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift.
Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
Lead cross-functional technical reviews for new AI deployments, ensuring security, data governance, and compliance standards are met.
Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.

Qualifications

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years developing AI/ML algorithms or technologies, or a Master’s degree plus at least 2 years developing AI/ML algorithms or technologies.
At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.

Preferred experience

Experience leading development of AI systems with tradeoffs across cost, latency, throughput, and accuracy.
6 years deploying scalable and responsible AI solutions on cloud platforms such as AWS, Google Cloud, Azure, or equivalent private cloud.
Experience designing, developing, delivering, and supporting AI services.
Experience building AI/ML algorithms and services (for example: LLM inference, similarity search and vector databases, guardrails, memory) using Python, C++, C#, Java, CUDA, or Golang.
Experience optimizing training and inference software for improved hardware utilization, latency, throughput, and cost.
Experience developing agentic AI systems and agentic workflows.
Ability to apply new AI research and systems judiciously in production.
Proficiency designing distributed systems for model training, evaluation, and online inference at petabyte scale.
Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules.
Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

Tools and technologies you may work with

AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
Python, Go, Scala, CUDA, Java
AWS, Google Cloud, Azure
C++, C#, Golang

Location and compensation

San Jose, CA (onsite) | USD 215,200 - 245,600 per year. Performance-based incentive compensation may be available, including cash bonus(es) and/or long term incentives (LTI).

Capital One also offers a comprehensive, competitive, and inclusive set of health, financial, and other benefits that support your total well-being.

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Today

AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)

Capital One San Jose, CA

San Jose, CA

Today

$215k - $246k/yr Full time Agentic Ai Orchestration Ai Engineer Artificial Intelligence

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Job Description

Capital One is hiring an AI Engineer 4 on the Intelligent Foundations and Experiences (IFX) team to build and deploy responsible, scalable AI systems and platform services. This onsite role in San Jose focuses on foundation model training, LLM inference, agentic workflows, evaluation and governance, observability, and optimization for performance and cost.

Responsibilities

Work with cross-functional partners including engineers, research scientists, technical program managers, and product managers to deliver AI-powered products for associates and customers.
Design, develop, test, deploy, and support AI software components such as foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability.
Use a stack of Open Source and SaaS AI technologies including AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and additional tools.
Develop and introduce foundation model optimization techniques to improve scalability, cost, latency, and throughput for production AI systems.
Help shape the technical vision and long-term roadmap for foundational AI systems at Capital One.
Own end-to-end architecture for complex AI systems, with focus on maintainability, observability, and ethical alignment.
Define and maintain service-level objectives (SLOs) for AI reliability across latency, uptime, and model performance drift.
Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines.
Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are addressed.
Mentor Principal and Senior Associates on scalable design, performance tuning, and research-to-production translation.

Requirements

Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 4 years of experience developing AI and ML algorithms or technologies, or
Master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 2 years of experience developing AI and ML algorithms or technologies.
At least 4 years of programming experience with Python, Go, Scala, CUDA, or Java.

Technologies

AWS Ultraclusters, Huggingface, VectorDBs, PyTorch
AWS, Google Cloud, Azure
Python, Go, Scala, CUDA, Java, C++, C#, C# (listed as provided), Golang
GPU, TPU

Benefits

Performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI).
Comprehensive, competitive, and inclusive set of health, financial and other benefits.

Preferred Qualifications

Experience leading development AI systems with tradeoff decisions across cost, latency, throughput, and accuracy.
6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud).
Experience designing, developing, delivering, and supporting AI services.
Experience developing AI and ML algorithms or technologies such as LLM Inference, Similarity Search and VectorDBs, Guardrails, and Memory using Python, C++, C#, Java, CUDA, or Golang.
Experience developing and applying state-of-the-art optimization techniques for training and inference software to improve hardware utilization, latency, throughput, and cost.
Experience building agentic AI systems and agentic workflows.
Passion for staying abreast of the latest AI research and systems, and applying novel techniques in production.
Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale.
Experience defining AI model governance processes including producibility, lineage tracking, and automated retention schedules.
Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms.

Team Description

The Intelligent Foundations and Experiences (IFX) team is at the center of bringing Capital One’s AI vision to life.
The team partners across the company to advance the state of the art in science and AI engineering, building and deploying proprietary solutions central to the business.
AI models and platforms empower teams across Capital One to enhance products with responsible and scalable AI for high-leverage impact.

Staff Machine Learning Engineer, ML Platform

Braze Chicago, IL

Chicago, IL

Today

$184k - $314k/yr Full time Ai Ml Artificial Intelligence Automation

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Job Description

Braze is hiring a Staff Machine Learning Engineer for the Predictive and Generative AI (PGAI) team to own the ML platform underneath production ML and drive reliability at global scale.

Responsibilities

Identify and lead major initiatives that change production ML operations, including replatforming queueing and orchestration, overhauling deployment and cloud identity, or retiring infrastructure components
Ship high-impact infrastructure and ML platform changes at high velocity, with direct hands-on ownership of complex initiatives from design through production
Own the platform technical vision and production quality bar, including direction for training, deployment, serving, and observability
Lead incident response for ML systems and drive reliability and cost improvements to keep the platform efficient at scale
Coordinate and deliver cross-team initiatives leveraging shared infrastructure, deployment tooling, and data systems owned with partner teams
Improve engineering quality through design review, code review, and production readiness practices for ML systems
Mentor other senior engineers and data scientists
Translate technical decisions into customer and business outcomes and represent the team’s technical perspective to product and engineering leadership

Requirements

8+ years building and operating distributed systems in production, with depth in deployment and operations
Hands-on production experience with ML workloads
Proven technical leadership: owned team direction, led multi-quarter initiatives across team boundaries, and grew senior engineers while maintaining high personal output
Deep working knowledge of Kubernetes and cloud infrastructure, including identity and access management, networking, and the cost profile of workloads
Strong verbal and written communication skills, able to build consensus and drive forward decision-making
Bonus: Experience with queueing and orchestration systems such as Celery, RabbitMQ, Kafka, or Ray
Bonus: Experience with ML platform tooling such as MLflow or other model registry tools, feature stores, or ML observability
Bonus: Experience with Braze stack: Python, Ruby on Rails, MongoDB, Redis, Kubernetes
Bonus: Experience operating under compliance regimes such as SOX or HIPAA
Bonus: Experience in customer engagement, personalization, or marketing technology domains

Technology Focus

Celery, RabbitMQ, Kafka, Ray
MLflow
Python, Ruby on Rails
MongoDB, Redis
Kubernetes
SOX, HIPAA

Location and Compensation

Location: Chicago, IL (hybrid)
Salary: USD 184,000 - 314,000 per year
Minimum experience: 8 years

Benefits

Competitive compensation that may include equity
Retirement and Employee Stock Purchase Plans
Flexible paid time off
Comprehensive benefit plans covering medical, dental, vision, life, and disability
Family services including fertility benefits and equal paid parental leave
Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
Curated in-office employee experience designed to foster community, team connections, and innovation
Opportunities to give back, including annual Volunteer Week and donation matching
Employee Resource Groups
Collaborative, transparent, and fun culture recognized as a Great Place to Work®

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Today

Machine Learning Engineer - Multimodal Intelligence

Apple Seattle, WA

Seattle, WA

Today

$142k - $263k/yr Full time Ai Ml Artificial Intelligence Data Pipeline

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Job Description

Apple’s Multimodal Intelligence team is hiring a Machine Learning Engineer to operationalize multimodal foundation models into production-grade Apple Intelligence features.

Responsibilities

Build pipelines, infrastructure, and production systems that enable multimodal foundation models to ship as Apple Intelligence features.
Own end-to-end model delivery, including:
- Data curation and scaling training pipelines.
- Fine-tuning and optimization of large multimodal models for on-device and hybrid execution.
- Reproducible evaluation and regression testing for text and visual understanding.
- Hardening candidate approaches into robust, maintainable production systems under real latency, memory, power, and privacy constraints.
Partner with modeling, platform, hardware, and product engineering teams across Apple and incorporate future hardware design and product needs into implementation decisions.
Collaborate across teams to deliver high-quality product outcomes.

Requirements

Master’s or PhD, or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or a related technical field.
Deep expertise in multimodal foundation models with a focus on practical applications.
Proven ability to translate research into practical applications via published work or industry experience.
Applied research experience in at least one major area of model development (data curation, pre-training, fine-tuning, alignment, or evaluation), especially for multimodal systems.
Experience building large-scale training pipelines, working with large datasets, and scaling models across distributed systems.
Experience bridging research ideas with production constraints.
Deep learning experience with documented work in at least one multimodal area such as vision, language, video, or audio.
Proficiency in Python and a modern deep learning framework: PyTorch or JAX.
Experience with rapid prototyping, reproduction, and validation of research ideas.
Ability to work in a collaborative environment.
Ability to communicate analysis results clearly and effectively.
BS and a minimum of 3 years of relevant industry experience.

Technologies

Python
PyTorch
JAX

Compensation

Base pay range: $142,300 - $263,300 per year.
Base pay depends on skills, qualifications, experience, and location.

Benefits

Comprehensive medical and dental coverage.
Retirement benefits.
Discounted products and free services.
Reimbursement for certain educational expenses, including tuition.
Discretionary restricted stock unit awards.
Employee Stock Purchase Plan: ability for eligible employees to purchase Apple stock at a discount if voluntarily participating.
Discretionary employee stock programs that offer an opportunity to become an Apple shareholder.
Discretionary bonuses or commission payments, and relocation (eligibility may apply).

Location: Seattle, WA (onsite)

Salary: USD 142,300 - 263,300 per year

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1d ago

Senior Machine Learning Engineer

Adobe San Jose, CA

San Jose, CA

1d ago

$152k - $265k/yr Full time AI Application Security Artificial Intelligence

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Job Description

As part of Adobe’s Search, Discovery & Content AI (SDC) team, you will help design and deliver large-scale machine learning systems that support generative AI and content understanding and discovery used by millions of people. This is a hands-on role spanning end-to-end system design through deployment and ongoing optimization, with opportunities to build GPU-optimized modeling and ML pipeline platform capabilities, while working closely with architects, product, and engineering teams.

What you’ll do

Define and develop end-to-end machine learning systems using innovative architectures
Develop and implement scalable, GPU-optimized modeling algorithms that can operate on large-scale data in production environments
Build and maintain high-performance, scalable, maintainable platform features across the complete ML pipeline
Partner with architects, product management, and engineering teams to translate product requirements into technical solutions
Design and develop runtimes and libraries for emerging ML technologies to help keep the team at the forefront of the field
Contribute to creation of detailed requirements and design documents for features across the technology stack

What you bring

PhD or master’s degree in computer engineering, Computer Science, Computer Vision, Robotics, or a related field (or equivalent experience)
Deep understanding of generative AI, deep learning, computer vision, and recommendation systems, with a track record applying these methods to complex problems
Proficiency with ML frameworks and tools such as Scikit-learn, Hugging Face, PyTorch, and PyTorch Lightning
Expertise with cloud technologies, Docker, and containerization
Experience with AWS, Microsoft Azure, or equivalent cloud platforms
Proficiency in one or more programming languages including Python, C++, Java, and Rust
Exceptional analytical and quantitative problem-solving skills
Excellent communication and relationship-building skills
Demonstrated ability to thrive in a collaborative team environment

Tools and technologies

Scikit-learn, Hugging Face, PyTorch, PyTorch Lightning
Docker, AWS, Microsoft Azure
Python, C++, Java, Rust

Interview AI use notice

The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

Pay range

U.S.: $151,800 - $265,350 annually.

California: $183,300 - $265,350 annually.

Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP). In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

State-specific notices

California: Fair Chance Ordinances. Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Colorado: Application Window Notice. If this role is open to hiring in Colorado, the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If Colorado is not listed, no specific application window applies and the posting may close based on hiring needs.
Massachusetts: Massachusetts Legal Notice. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment.

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1d ago

AI/Machine Learning Engineer SME

Integration Innovation, Inc. (i3) Washington, DC

Washington, DC

1d ago

$200k - $350k/yr Full time Artificial Intelligence Data Architecture Data Engineer

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Job Description

SME-level AI/Machine Learning Engineer to architect enterprise-ready AI/ML solutions for the Defense Intelligence Agency (DIA) Enterprise Data Management & Analytics (EDMA) effort.

Responsibilities

Architect enterprise-ready AI/ML solutions, covering model-training pipelines, inference services, feature stores, data-ingestion pathways, and MLOps frameworks aligned to requirements
Define the technical roadmap by translating complex mission needs into actionable architectures, workstreams, and implementation plans
Lead multi-disciplinary engineering teams, directing algorithms, model selection, data strategy, integration, and delivery cadence
Oversee sprint planning and technical execution to keep deliverables on schedule, clear blockers, and ensure engineering artifacts meet enterprise standards
Act as the primary technical interface with government stakeholders, explaining architecture decisions, model behaviors, risk tradeoffs, and recommended solution pathways
Establish and enforce best practices across ML engineering, DevSecOps, coding standards, test automation, and model life-cycle governance
Run technical reviews and mentor engineers to raise team capability and maintain alignment to mission outcomes
Guide evaluation and adoption of advanced ML tools and approaches, including PyTorch, TensorFlow, JAX, distributed compute, MLOps platforms, generative-AI modernization patterns, and enterprise-scale data solutions
Integrate AI capabilities into cloud-native or hybrid architectures while meeting security, accreditation, and enterprise data management requirements
Provide SME support for strategic planning, including solution briefs, architecture diagrams, CONOPS development, and decision-ready artifacts for government review panels
Champion responsible-AI and governance aligned to IC and DoD directives

Requirements

U.S. Citizenship
Active Secret clearance with the ability to obtain and maintain TS/SCI
Bachelor’s degree (Master’s preferred) in Computer Science, Engineering, Applied Mathematics, Data Science, or a related field
Minimum 14 years of progressive experience in AI/ML, data engineering, or advanced analytics
Demonstrated experience architecting and deploying enterprise AI/ML systems
Deep proficiency in Python and modern ML frameworks, including PyTorch, TensorFlow, and JAX
Experience leading technical teams, performing architecture trade studies, and guiding development across the full ML life cycle
Strong understanding of secure software engineering, distributed systems, DevSecOps, and containerization
Excellent communication skills and ability to interface with senior government stakeholders

Technologies

Python
PyTorch
TensorFlow
JAX
MLOps
DevSecOps

Preferred Qualifications

Experience supporting AI/ML projects in government, defense, or intelligence environments
Familiarity with Intelligence Community mission needs and data types
Exposure to cloud-native development (AWS, Azure, GovCloud)
Experience building or supporting NLP, computer-vision, generative-AI, or anomaly-detection models
Knowledge of MLOps, CI/CD, container orchestration, or distributed training frameworks

Location: Washington, DC (hybrid)

Salary: USD 200,000 - 350,000 per year

Company: Integration Innovation, Inc. (i3)

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2d ago

Senior Machine Learning Engineer, Developer AI

ByteDance San Jose, CA

San Jose, CA

2d ago

$218k - $480k/yr Full time Python Agentic Ai Ai Agent

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Job Description

Context: ByteDance’s Dev Infra team is building Dev AI systems to improve software engineering productivity at scale, and this Senior Machine Learning Engineer role supports that mission.

Responsibilities

Develop and enhance machine learning and large language model systems for software engineering tasks, including code generation, unit test generation, and debugging.
Build AI-powered developer agents and intelligent workflows that reason over large codebases and use development environments and tools to execute multi-step engineering tasks.
Support engineers across the software development lifecycle with agentic assistance and tool interaction.
Improve model and agent performance using prompt engineering, context engineering, retrieval, fine-tuning, reinforcement learning, tool-use design, and agent harness engineering.
Create high-quality training and evaluation data pipelines for software engineering use cases, including data collection, filtering, synthesis, labeling, and hard-example mining.
Apply advances in large language models, code intelligence, program analysis, reinforcement learning, and autonomous software engineering to real-world developer productivity problems at scale.

Requirements

Bachelor’s degree or above in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, or a related field.
5+ years of relevant industry or research experience in machine learning, large language models, code intelligence, AI-powered developer tools, or related areas.
Strong programming skills in one or more of: Python, Go, Java, C++, JavaScript, TypeScript.
Solid understanding of data structures, algorithms, machine learning, operating systems, databases, and fundamental system design principles.
Experience owning complex ML projects end-to-end, from problem formulation and data construction through model development, evaluation, deployment, and production iteration.
Strong system design and engineering skills, including building scalable, reliable, and efficient machine learning systems or AI-powered applications.
Strong communication and collaboration skills, including ability to drive complex technical projects across teams.

Technologies

Python
Go
Java
C++
JavaScript
TypeScript

Preferred Qualifications

Experience building or leading AI systems for software engineering, including code generation, coding agents, unit test generation, debugging, or code review.
Deep experience with large language models and one or more post-training/model improvement techniques such as supervised fine-tuning, reinforcement learning, preference optimization, prompt engineering, context engineering, retrieval, or model evaluation.
Experience designing and improving agentic systems, including tool-using LLMs, coding agents, agent harnesses, MCP, agent skills, planning, memory, or multi-step execution workflows.
Experience building large-scale training data, evaluation datasets, benchmarks, or experimentation pipelines for machine learning or code intelligence systems.
Strong understanding of software engineering and code intelligence techniques such as program analysis, compilers, static analysis, code search, repository indexing, testing, and debugging.
Publications, patents, open-source contributions, or demonstrated technical leadership in machine learning, large language models, code intelligence, developer tools, or AI for software engineering.

Compensation

Base salary range: USD 218,400 - 480,000 per year (city-specific, selected city).
Compensation description: base salary range for the selected city is $218400 - $480000 annually.

Benefits

Day one access to medical, dental, and vision insurance.
401(k) savings plan with company match.
Paid parental leave.
Short-term and long-term disability coverage.
Life insurance.
Wellbeing benefits.
10 paid holidays per year.
10 paid sick days per year.
17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
Additional discretionary bonuses/incentives and restricted stock units (role may be eligible).

Location

San Jose, CA (onsite)

Fair Chance Ordinance (Los Angeles County, Unincorporated)

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Company believes criminal history may have a direct, adverse, and negative relationship on job duties, potentially resulting in withdrawal of a conditional offer.
Examples of job duties include: interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues; handling and managing confidential information including proprietary and trade secret information and access to IT systems; exercising sound judgment.

Reasonable Accommodation

ByteDance is committed to providing reasonable accommodations in recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs, or other reasons protected by applicable laws.
For assistance or a reasonable accommodation, contact: https://tinyurl.com/RA-request

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Machine Learning Engineering Jobs

AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)

AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)

Staff Machine Learning Engineer, ML Platform

Machine Learning Engineer - Multimodal Intelligence

Senior Machine Learning Engineer

AI/Machine Learning Engineer SME

Senior Machine Learning Engineer, Developer AI

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