Machine Learning Solutions Engineer

Apple; Cupertino (CA); On-site; USD 175,000 - 313,000; Full time

Job summary

An established industry player is seeking a talented Machine Learning Solutions Engineer to bridge the gap between advanced machine learning technologies and user-facing products. In this dynamic role, you will collaborate with ML researchers, software engineers, and product managers to develop production-ready AI systems that deliver real business value. Your expertise in integrating machine learning capabilities into software products will be crucial as you prototype features, evaluate their feasibility, and guide implementation processes. Join a forward-thinking company where your contributions will enhance user experiences and drive innovation in the tech landscape.

Benefits

Comprehensive medical and dental coverage

Retirement benefits

Discounted products and free services

Educational reimbursement

Discretionary bonuses

Employee stock purchase plan

Qualifications

• 5+ years of experience integrating ML capabilities into software products.
• Strong programming skills in Python and experience with ML frameworks.

Responsibilities

• Collaborate with cross-functional teams to build production-ready AI systems.
• Prototype ML-powered features and evaluate their business impact.

Skills

Python

Machine Learning

ML frameworks

Large Language Models (LLMs)

A/B testing

Communication Skills

Education

Bachelor's degree in Computer Science

Master's degree in Machine Learning

Tools

Retrieval Augmented Generation (RAG)

Job description

Machine Learning Solutions Engineer

Cupertino, California, United States Software and Services

Summary

Posted: Apr 12, 2025

Role Number: 200598748

Our team bridges the gap between machine learning capabilities and user-facing products. We transform advanced ML technologies into valuable features that solve real customer problems. We're looking for a skilled Machine Learning Solutions Engineer who can work at the intersection of ML research, engineering, and product development to build production-ready AI systems that deliver measurable business value. If you're excited about making ML models work in real-world applications and can collaborate effectively across technical and non-technical teams, we'd love to talk with you!

Description

As a Machine Learning Solutions Engineer, you'll play a crucial role in our ML product development lifecycle. You'll collaborate with ML researchers, software engineers, product managers, and designers. You'll be responsible for prototyping ML-powered features, evaluating their technical feasibility and business impact, and guiding the implementation process. In this role, you will build proof-of-concepts that demonstrate ML capabilities in practical contexts, develop strategies for measuring product value, design effective evaluation frameworks, and help create seamless transitions between different ML models as technologies evolve. You'll need to think holistically about how ML systems fit into larger product ecosystems and user workflows. You will be successful in our team if you enjoy solving complex technical problems with a product mindset, can communicate effectively with diverse stakeholders, and thrive at finding the right balance between ML performance and product requirements. This role requires both technical depth and the ability to see the big picture of how ML creates value for users.

Minimum Qualifications

1. Bachelor's degree in Computer Science, Machine Learning, or a related technical field
2. 5+ years of industry experience with 2+ years of experience integrating ML capabilities into software products
3. Experience gathering and synthesizing customer feedback to inform ML product development and feature prioritization
4. Demonstrated ability to translate user needs into technical requirements for ML solutions
5. Strong programming skills in Python and experience with ML frameworks
6. Experience with prototyping, measuring, and iterating on ML-powered features
7. Experience with Large Language Models (LLMs) and understanding how to effectively integrate them into products

Preferred Qualifications

1. Practical knowledge of Retrieval Augmented Generation (RAG) systems and their applications
2. Experience designing and implementing ML evaluation frameworks that connect to product success metrics
3. Familiarity with A/B testing and experimental design for ML features
4. Background in developing successful POC-to-production rollout strategies for ML features
5. Experience collaborating with cross-functional teams including product management, design, and engineering
6. Demonstrated ability to balance technical trade-offs with product requirements
7. Excellent communication skills with the ability to explain technical concepts to non-technical stakeholders

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 $175,800 and $312,200, 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.

Equal Opportunity Employer

Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.