425 jobs for "GenAI Engineer"

Machine Learning Scientist - Apple Services Engineering, GenAI & ML Frameworks

At Apple - New York City

Posted on Oct 11

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Senior Machine Learning Engineer I - GenAI Applications

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Sr. Staff Engineer (GenAI)

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Sr Software Engineer, GenAI Platform & Practice

At Apple - Cupertino

Posted on Oct 8

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Lead Software Engineer - Python - GenAI

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Project GenAI Engineer III

At Deloitte - Rosslyn

Posted on Aug 26

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Director, Software Engineering (14+ years, Scala, Spark, Data Pipeline, GenAI) Spark,

At Visa - Bengaluru

Posted on Oct 6

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Senior Engineer - GenAI Security

At Bank of America - New York · Pennington

Posted on Jun 8

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Full-Stack Engineer 4 (Java, Spring, DynamoDB, S3, GraphQL, GenAI)

At Capital One - New York · McLean

Posted on Sep 25

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Staff SW Engineer- Java Full stack with GenAI experience

At Visa - Bengaluru

Posted on Oct 1

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AI Engineer 5 (GenAI Platform, Agentic Infrastructure)

At Capital One - San Jose · San Francisco

Posted on Sep 24

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Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)

At Capital One - New York · San Francisco

Posted on Sep 24

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Sr. Manager, Software Engineering (10 to 14 years, GenAI)

At Visa - Bengaluru

Posted on Sep 25

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Software Development Engineer III - GenAI

At GM Financial - Irving

Posted on Aug 11

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Senior AI Engineer (GenAI)

At Kyndryl - Remote / Flexible

Posted on Oct 1

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Software Engineer, GenAI Platform

At Roblox - San Mateo

Posted on Sep 25

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Senior Staff Machine Learning Engineer, GenAI Platform

At Reddit - Remote / Flexible

Posted on Apr 1

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Staff Software Engineer, GenAI

At Agoda

Posted on Oct 8

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GenAI Physical Synthesis Engineer

At Apple - Austin

Posted on Oct 17

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Full Stack Engineer 4- People Tech- GenAI & Agentic Systems (LangChain, LangGraph)

At Capital One - McLean · Richmond

Posted on Sep 23

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Apple

Machine Learning Scientist - Apple Services Engineering, GenAI & ML Frameworks

New York City, NY$184,700 – $324,800Posted 27 days ago

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Apple Services GenAI & ML Frameworks team aims at bridging foundation model capabilities with real-world production systems. The work spans LLM continual pretraining, posttraining, agentic reinforcement learning, agentic system optimization etc.. This role is part of the cross-LOB effort to support various GenAI use cases across ASE, and specializes in improving LLM domain knowledge, tool use, reasoning, and system integration-working closely with product, infra, and foundation model teams to bring cutting-edge models into user-facing features at scale.

Description

We are seeking a strong candidate who can operate end-to-end across model development and production integration-someone equally strong in (1) LLM training (domain-adaptive continual pretraining, post-training, preference optimization / RL such as GRPO-style methods), (2) agentic systems (tool schemas, multi-turn reliability, rubric- or verifier-based learning loops), and (3) deployment-aware optimization (latency/cost/reliability tradeoffs, evaluation harnesses, and iterative improvement from production signals).

The ideal candidate has a track record of turning LLM research into shipped capabilities, can partner effectively with product, infra, and foundation model teams, and can lead ambiguous cross-LOB initiatives from problem definition through execution and scaling. Experience building robust tooling around synthetic data generation, eval, and training pipelines for LLMs is strongly preferred, since this role is expected to raise the bar on both research velocity and production readiness.

Preferred Qualifications

PhD in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

Minimum Qualifications

BS/MS in a quantitative field, including Computer Science, Maths, Statistics, Physics, etc.

3+ years of relevant work experience

Proficient programming skills in Python

Hands-on experience working with deep learning toolkits such as Jax, Tensorflow or PyTorch

Proven track record in training or deployment of large models or building large-scale distributed systems

Deep understanding of Deep Learning and Large Language Models (LLMs)

Natural Language Processing

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology

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