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Machine Learning Ai Developer Jobs in Massachusetts

Amazon

Machine Learning Engineer, Alexa AI

Boston, MA · On-site

The Alexa AI team is looking for a passionate, talented, and inventive Machine Learning Engineer with a strong machine learning background, to build capabilities such as fine tuning, distillation ...

Apple Inc.

Machine Learning Engineer - Health AIML

Cambridge, MA · On-site

$194.70 - $354.70/hr

  • Medical

  • Dental

  • Retirement

Cambridge, Massachusetts, United States Machine Learning and AI The Health AI team is at the ... We are looking for a senior engineer excited about solving real-world problems in the health domain ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... The Logistics AI group is responsible for the intelligence and execution behind Instacart ...

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Machine Learning Ai Developer information

What is the difference between Machine Learning Ai Developer vs Data Scientist?

AspectMachine Learning Ai DeveloperData Scientist
CredentialsBachelor's or higher in CS, AI, or related fields; certifications in ML/AIBachelor's or higher in CS, Statistics, or related fields; certifications in data analysis or ML
Work EnvironmentDevelops AI models, algorithms, and applications; often in tech companies or R&DAnalyzes data, builds models, and provides insights; in various industries including finance, healthcare
Industry UsagePrimarily in AI product development, software, and tech firmsAcross industries for data analysis, business intelligence, and decision-making

While both roles require knowledge of machine learning and programming, Machine Learning Ai Developers focus on creating and deploying AI models and applications, whereas Data Scientists analyze data to extract insights and inform business strategies. The roles often overlap but differ in primary focus and application.

Is machine learning AI developer a good career?

A machine learning AI developer is a highly in-demand role that involves designing algorithms and models to enable machines to learn from data. It offers strong job growth, competitive salaries, and opportunities across various industries such as technology, healthcare, and finance. Success in this field typically requires skills in programming, mathematics, and familiarity with tools like Python and TensorFlow.

What does a machine learning AI developer do?

A machine learning AI developer designs, builds, and maintains algorithms and models that enable computers to learn from data and make predictions or decisions. They work with programming languages like Python or R, utilize frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists and engineers to deploy AI solutions in various applications.

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What job categories do people searching Machine Learning Ai Developer jobs in Massachusetts look for?

The top searched job categories for Machine Learning Ai Developer jobs in Massachusetts are:

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Cities in Massachusetts with the most Machine Learning Ai Developer job openings:

Machine Learning Ai Developer jobs near you

Senior Machine Learning Engineer, AI Platform

WHOOP

Boston, MA • On-site

$133K - $175K/yr

Full-time

Re-posted 16 days ago

Job description

Job Summary:
WHOOP is on a mission to unlock human performance and healthspan, empowering members through AI-driven insights. They are seeking a Senior Machine Learning Engineer to scale the intelligence layer of their AI platform, focusing on core components that enhance member experiences and improve AI systems.
Responsibilities:
• Design, build, and operate production AI systems and scaffolding around language models that power conversational, predictive, and generative capabilities across WHOOP products.
• Lead end-to-end AI system initiatives spanning problem definition, data flows, dataset design, evaluation harnesses, deployment, and iteration in close partnership with data science and product.
• Build and maintain pipelines for collecting, curating, and reshaping messy, multi-source data into high-quality, well-structured training and evaluation datasets for language model–based systems.
• Operationalize fine-tuning and evaluation workflows for large language models behind member-facing features such as WHOOP Coach and AI Support, including defining datasets, labels, and taxonomies that reflect real member needs.
• Develop tooling and frameworks that make experimentation, offline/online evaluation, and model deployment faster, safer, and more repeatable, including robust observability for AI features in production.
• Build and maintain feedback loops that connect real member interactions, offline evaluations, and training data updates so that models improve continuously based on real-world behavior.
• Mentor other engineers and data scientists, share best practices in applied AI/ML, and help elevate the overall technical bar of the AI Platform team.
Qualifications:
Required:
• 3+ years of experience in applied machine learning, AI engineering, or ML-focused software engineering roles, including significant work in production environments.
• Hands-on experience building with modern language models (open-weight or API-based), including prompt design, fine-tuning, and rigorous evaluation.
• Solid working understanding of ML fundamentals (dataset construction, feature engineering, training workflows, evaluation metrics, experiment design) sufficient to make good engineering tradeoffs and partner effectively with data scientists.
• Familiarity with modern LLM training and alignment techniques such as supervised fine-tuning (SFT), direct preference optimization (DPO), and reinforcement learning (RL), and how they influence data requirements, evaluation strategies, and system design in production.
• Proven track record building, shipping, and operating ML-powered systems end to end, from data pipelines (batch and/or streaming) that transform large datasets into usable training and evaluation sets to production deployments with inference optimization, observability, and lifecycle management.
• Strong proficiency in data manipulation and analysis, including working with messy, multi-source, and semi-structured data and translating product questions into well-defined datasets, labels, and evaluation splits.
• Familiarity with best practices for secure, privacy-aware AI and working with sensitive data.
• Excellent communication and collaboration skills, with the ability to influence across teams and drive alignment on technical direction.
Company:
WHOOP provides wearable fitness technology and a subscription platform that tracks physiological data for health and performance insights. Founded in 2012, the company is headquartered in Boston, USA, with a team of 501-1000 employees. The company is currently Late Stage.
Whoop logo

About Whoop

Sourced by ZipRecruiter

At WHOOP, we're on a mission to unlock human performance. WHOOP empowers users (Olympians, Professional Athletes, Fitness Enthusiasts, etc) to perform at a higher level through a deeper understanding of their bodies and daily lives.

Industry

Fitness and sports centers

Company size

501 - 1,000 Employees

Headquarters location

Boston, MA, US

Year founded

2012

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