400 jobs for "Senior Technical Product Manager"

AIML - Sr Machine Learning Engineering Manager, Evaluation

At Apple - Cupertino

Posted on Oct 17

View job Apply on company site

Operations Program Manager - Product Operations

At Apple - Bengaluru

Posted on Oct 16

View job Apply on company site

Senior Technical Developer, Global Apparel Graphics - PCC

At Nike - Beaverton

Posted on Oct 29

View job Apply on company site

Sr. Data Scientist, Apple Business & Education Organization

At Apple - Cupertino

Posted on Oct 10

View job Apply on company site

Senior, 3D Designer, Innovation

At Nike - Beaverton

Posted on Nov 4

View job Apply on company site

Engineering Program Manager

At Apple

Posted on Oct 15

View job Apply on company site

Engineering Program Manager

At Apple

Posted on Oct 2

View job Apply on company site

Procurement Manager

At Spectrum - Greenwood Village

Posted on Oct 24

View job Apply on company site

Manager, Account Management - Adyen for Platforms

At Adyen - New York

Posted on Nov 3

View job Apply on company site

Input/Output (I/O) Systems Quality Engineering Manager

At Apple - Minato

Posted on Oct 19

View job Apply on company site

Input/Output (I/O) Systems Quality Engineering Manager

At Apple - Minato-ku

Posted on Oct 19

View job Apply on company site

Software Engineering Manager (Cross Platform Faces) - Watch Software

At Apple - Cupertino

Posted on Oct 16

View job Apply on company site

Offensive Security Research Manager

At Apple - Paris

Posted on Oct 11

View job Apply on company site

Senior Application Developer

At Cargill - Bengaluru

Posted on Nov 6

View job Apply on company site

Senior Data Engineer

At Adyen - Amsterdam

Posted on Nov 6

View job Apply on company site

Senior Software Engineer - Full Stack

At Capital One

Posted on Oct 31

View job Apply on company site

Senior Specialist, Product Experience Design

At Mastercard - Toronto

Posted on Oct 24

View job Apply on company site

Senior Software Engineering - Ag & Trading

At Cargill - Bengaluru · Shanghai

Posted on Oct 21

View job Apply on company site

Senior Software Engineer

At Mastercard - Arlington

Posted on Oct 20

View job Apply on company site

Senior Machine Learning Engineer, Proactive

At Apple - Santa Clara

Posted on Oct 19

View job Apply on company site

Apple

AIML - Sr Machine Learning Engineering Manager, Evaluation

Cupertino, CA$237,600 – $401,700Posted 23 days ago

Apply on company site View full job

Why you should apply for a job to Apple:

Ranked as one of the Best Technology Companies in 2020
3.7/5 in overall job satisfaction
3.1/5 in supportive management
66% say women are treated fairly and equally to men
65% would recommend this company to other women
66% say the CEO supports gender diversity

Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›

Apple's AIML Evaluation team builds the systems and methodologies that measure and improve the quality of foundation models and agentic experiences. We are looking for a senior, hands-on Machine Learning Engineering Manager to lead a small team working at the intersection of model evaluation, agent optimization, and data generation. In this role, you will help define how evaluation closes the loop with model and product development, turning observed quality gaps into targeted improvements to prompts, agent harnesses, datasets, and models.

You will combine technical depth with people leadership. You should be comfortable moving from research papers and experimental results to production-quality ML pipelines, while mentoring engineers and aligning teams around a clear technical direction. Your work will span Apple Foundation Models and product teams, with the goal of creating repeatable evaluation and refinement loops that improve the quality of Apple intelligence experiences.

Description

As a Senior Machine Learning Engineering Manager in AIML Evaluation, you will lead the technical strategy and execution for agent evaluation and automatic optimization. You will own systems that evaluate foundation models and agents, diagnose failure modes, and use those signals to drive automated prompt, context, tool, rubric, and agent-harness improvements. You will also help establish the interfaces between evaluation and post-training so that high-value failures can be converted into targeted data, environments, reward signals, and measurable model improvements.

This is a hands-on leadership role. You will prototype new approaches, participate in architecture and code reviews, design experiments, and help your team translate emerging research into scalable evaluation and optimization pipelines. You will partner closely with Apple Foundation Models, product engineering teams, and other AIML groups to build an evaluation flywheel that connects real product behavior with model and agent refinement. You will also work across the organization to advance synthetic data generation for both evaluation and post-training, with strong attention to data quality, representativeness, privacy, and reproducibility.","responsibilities":"Architects and builds scalable evaluation systems for foundation models and agents, including benchmarks, LLM-based evaluators, simulation environments, trajectory analysis, and regression testing.

Establishes an end-to-end evaluation flywheel with Apple Foundation Models and product teams that connects observed failures to diagnosis, targeted refinement, post-training, and measurable quality improvement.

Leads, mentors, and grows a small team of machine learning engineers while remaining deeply involved in technical design, experimentation, implementation, and review.

Defines the technical strategy and roadmap for automatic prompt, context, tool, rubric, and agent-harness optimization for agentic development and model evaluation.

Develops methods that convert evaluation findings into actionable model-improvement signals, including targeted datasets, synthetic trajectories, reward or preference signals, and optimization objectives.

Partners across AIML to design and scale synthetic data generation pipelines for evaluation and post-training.

Applies and adapts recent research in LLM and agent evaluation, automatic optimization, LLM-as-judge, reward modeling, test-time search, and post-training to production-quality workflows.

Preferred Qualifications

Track record of applying recent machine learning research to production systems or high-impact product development.

Experience with automatic prompt or context optimization, agent-search methods, evaluator optimization, or multi-objective optimization for agentic systems.

Experience generating and evaluating synthetic datasets, tool-use trajectories, or multi-turn agent interactions, including methods for filtering, deduplication, diversity, and quality control.

Experience designing evaluation systems that combine offline benchmarks, simulation, human evaluation, and product- or usage-derived signals.

Experience with privacy-preserving or on-device machine learning and evaluation.

Demonstrated ability to influence technical strategy across organizational boundaries and communicate complex model-quality tradeoffs to senior technical leaders.

Minimum Qualifications

8+ years of professional experience in machine learning, applied research, or software engineering, including experience building production ML systems or large-scale experimentation platforms.

3+ years of technical leadership experience, including direct people management of machine learning or software engineers and a demonstrated ability to mentor and grow strong technical talent.

Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field.

Strong hands-on programming and software engineering skills, particularly in Python, with experience building reliable ML pipelines using modern machine learning or deep learning frameworks.

Deep experience with large language models or agentic systems, including evaluation of multi-turn behavior, tool use, planning, reasoning, or other action-taking workflows.

Experience building automated evaluation methods such as LLM-based judges, rubrics, reward models, simulation-based evaluation, or scalable benchmark infrastructure.

Experience with at least one model or agent refinement area such as automatic prompt or context optimization, post-training, preference optimization, reinforcement learning, or agent-harness optimization.

Excellent communication and collaboration skills, with demonstrated ability to align research, engineering, and product teams around ambiguous technical problems.

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 $237,600 and $401,700, 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: Manufacturing

View company profile