Machine Learning Engineer Jobs in New York, USA

<div class="content-intro"><h2>About us</h2> <div>PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.</div> <div>We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.</div></div><p><strong>Note: </strong>We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.</p> <h2><strong>Who We're Looking For</strong></h2> <p>As a Senior Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.</p> <p>You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.</p> <p>With at least 3 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.</p> <p><strong>Note:</strong> Due to the nature of our aerospace and defense work, this position is open to US citizens only.</p> <h2>This Role </h2> <p>As a Senior MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurabl

<div class="content-intro"><h2>About us</h2> <div>PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software.</div> <div>We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.</div></div><p><strong>Note: </strong>We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.</p> <h2><strong>Who We're Looking For</strong></h2> <p>As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.<br><br>You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.<br><br>With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.</p> <p><strong>Note:</strong> Due to the nature of our aerospace and defense work, this position is open to US citizens only.</p> <h2>This Role </h2> <p>As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.</p> <div><strong>What you will do </strong></div> <ul> <li>Work closely with our simulation engineers, data scientists and customers to deve

<p><strong><u>About Cubist</u></strong></p> <p>Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.</p> <p><strong><u>Role/Responsibilities:</u></strong></p> <p>We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team.</p> <p>This role will apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations, such as creating a production support AI agent that helps monitor production problems and suggest actions.</p> <p>This role will also work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.</p> <p><strong><u>Requirements: </u></strong></p> <ul> <li>PhD or PhD candidate in machine learning, computer science or other AI related research fields</li> <li>Experience with sequential modeling and time series forecasting using deep learning</li> <li>Experience with deep neural networks and representation learning</li> <li>Prior experience working in a data driven research environment</li> <li>Experience with translating mathematical models and algorithms into code</li> <li>Proficiency in programming languages such as Python and R</li> <li>Experience with machine learning software libraries such as TensorFlow or PyTorch</li> <li>Experience implementing Agent or Context engineering is strongly preferred</li> <li>Experience with natural language processing technology is strongly preferred</li> <li>Excellent analytical skills, with strong attention to detail</li> <li>Collaborative mindset with strong independent research ability</li> <li>Strong written and verbal communication skills</li> <li>Commitment to the highest ethical standards</li> </ul>

Machine Learning Engineer at Wirescreen. Apply via Ashby.

Machine Learning Engineer at Teleskope. Apply via Ashby.

Our mission on the Advertising Product & Technology team is to build a next generation advertising platform that aligns with our unique value proposition for audio and video. We work to scale the user experience for hundreds of millions of fans and hundreds of thousands of advertisers. This scale brings unique challenges as well as tremendous opportunities for our artists and creators. We are seeking a Senior Machine Learning Engineer to join the Supply Personalization squad. Supply Personalization focuses on optimizing the volume, timing, and types of ad loads a user receives. By leveraging data, machine learning, causal inference, and large scale online experimentation, we aim to uncover and learn the most effective strategies for enhancing user experiences and driving business outcomes.   We are looking for someone with strong expertise in data analysis, online experimentation techniques, and large-scale ML and engineering systems; someone who is motivated by user and business problems as much as they are by technical problems, and who thrives under ambiguity, experimentation, and iteration. You will work directly on an array of product features that drive the optimal user experience for our ads. You will collaborate with our cross-functional teams to ideate, develop, and own complex technical solutions on our ad services technology platforms. As someone who shares our passion for building innovative ad experiences, you'll have a direct impact on how the world uses Spotify.

<div class="content-intro"><p><strong>Who We Are</strong></p> <p>Good Inside is redefining parenting - not as something that should “just come naturally,” but as a skill to learn and practice. Founded by Dr. Becky Kennedy and Dr. Erica Belsky, we combine sturdy leadership with innovative technology to give parents personalized guidance, AI-powered support, and a global community.</p> <p>Our mission: help parents raise resilient, confident kids in a changing world. We’ve already reached millions, and we’re just getting started.  We’re refining our product and expanding our reach to empower even more families.</p> <p>We’re looking for bold, high-ownership problem-solvers who want to build something new, tackle big challenges, and be at the forefront of change.</p></div><h3><strong>The Opportunity</strong></h3> <p>Good Inside is seeking a Senior Machine Learning Engineer to join our Engineering team. This is <strong>not</strong> a research or data science role – we’re looking for a strong backend engineer who has hands-on experience shipping ML-powered features in production. You’ll work at the intersection of backend systems and machine learning, building the infrastructure and services that bring personalized, intelligent experiences to our users.</p> <p>You should be comfortable working with ML APIs, understanding core ML concepts, and integrating models into reliable, scalable backend systems. Your primary identity is as a software engineer – someone who writes clean, production-grade code – with the added ability to reason about ML systems and bring them to life in our product.</p> <p>You will collaborate closely with cross-functional partners, including product, design, mobile, and data teams, to build high-quality features that serve our users’ needs. Your ability to blend backend engineering excellence with practical ML knowledge will be essential as we continue to evolve and scale the Good Inside platform.</p> <p><strong>This role follows a hybrid schedule, with three in-office days each week at our Manhattan location.</strong></p> <h3><strong>What You’ll Own</strong></h3> <ul> <li>Design, build, and maintain backend services and APIs that power ML-driven features across the Good Inside platform</li> <li>Integrate and orchestrate ML models and third-party ML APIs (e.g., LLM providers, recommendation engines, embeddings services) into production systems</li> <li>Build data pipelines and infrastructure to support model serving, feature storage, and real-time personalization</li> <li>Collaborate closely with product, mobile, and design teams to translate ML capabilities into user-facing features</li> <li>Own the reliability, performance, and scalability of ML-adjacent backend s

Machine Learning Engineer - Fraud Risk at Rain. Apply via Ashby.

Machine Learning Engineer, Detection (NY) at Doppel. Apply via Ashby.

<h3><strong>SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we’re simplifying and modernizing the ticketing industry.</strong></h3> <p>SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. We have the product, vision, and team to make life better for performers, venues, and fans, and build a generational consumer brand in the process. All we’re missing is you.</p> <p>We are looking for Software Engineers with varying levels of experience to join SeatGeek’s R&D team.</p> <h3><strong>What you'll do</strong></h3> <ul> <li>Run a modern, containerized service-oriented architecture using industry-leading software development practices</li> <li>Ship code to production many times a day</li> <li>Solve complex performance problems, build a many-sided marketplace, empower a data-driven business and scale our software to support our booming business</li> <li>Build performant, beautiful, inclusive user interfaces that delight our users and enhance our brand</li> <li>Evaluate new technologies and improve our software stack to keep our technological edge</li> <li>Leverage cutting-edge AI tools to bring ideas to life faster than ever while upholding SeatGeek’s technical and product standards</li> <li>Work across team and discipline boundaries to develop the best product in our industry</li> </ul> <h3><strong>What you have</strong></h3> <ul> <li>Experience building business critical software in a fast-paced environment. We'll be interested in hearing about what you've built and how</li> <li>Experience solving complex technical challenges. SeatGeek engineers create custom solutions to unique ticketing problems, including high traffic onsales, interactive venue maps, inventory tracking, and event matching. We'll be excited to hear about challenging problems you've solved</li> <li>Passion for software craftsmanship and product. You have well-considered opinions about how software should work, and hold yourself and your code to a high standard</li> <li>A product mindset. You think beyond the code, about user experience, business impact, and what makes a great product tick</li> <li>Commitment to your teammates. You enjoy working with a diverse group of people with different experiences and take pride in mentoring and learning from others</li> </ul> <h3><strong>Our stack</strong></h3> <p>You do not need experience with all of these, but we thought you might be curious. What we care about is your experience, skills, and approach to problem solving. Tools can be learned.</p> <ul> <li><strong>Languages + Frameworks

Machine Learning Engineer at Finch legal. Apply via Ashby.

Senior Machine Learning Engineer, Relevance at Patreon. Apply via Ashby.

<p>At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.</p> <p>Machine Learning is at the heart of Lyft’s products and decision-making. Machine Learning Engineers at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges, from pricing and marketplace frameworks that ensure reliability and competitiveness, to agentic AI platforms that automate analytical workflows, to behavioral detection systems that protect the integrity of our network. We operate at the intersection of applied ML and real business impact, shipping models that directly influence revenue, rider experience, and partner trust.</p> <p>Lyft Business builds products that help organizations move the people who matter most—employees, customers, patients, and guests—easily and efficiently. Our offerings include Business Travel, Lyft Pass, and Concierge (for healthcare and non-healthcare rides), enabling companies to manage transportation at scale through APIs, integrations (e.g., Concur, Expensify), and dedicated tools. These platforms power high-impact B2B use cases across corporate travel, healthcare access, customer experience, and community programs.</p> <p>We're looking for a Machine Learning Engineer to design, build, and deploy ML systems across Lyft Business. This is a high-scope role: you won't be siloed into one problem area. Instead, you'll move across pricing algorithms, fraud and behavior detection, agentic AI systems, and emerging ML applications as the business evolves. You'll write production-quality code, own models end-to-end from prototyping through deployment, and collaborate closely with Data Scientists, Product Managers, and Software Engineers to translate complex business problems into scalable ML solutions.</p> <p>This role is ideal for someone who is technically versatile, energized by variety, and wants to see their work directly shape a large-scale business.</p> <h3><strong>Responsibilities:</strong></h3> <ul> <li>Develop and deploy ML models across multiple problem domains — including dynamic pricing, marketplace optimization, fraud detection, and anomaly/behavior detection — in production environments serving millions of rides</li> <li>Build and iterate on agentic AI systems (e.g., LLM-powered analytical agents) that automate decision-making and reduce operational overhead</li> <li>Design and implement feature pipelines, model training workflows, and serving infrastructure using Lyft's ML platform</li> <li>Partner with Data Scientists on the Algorithms and Decisions teams to take research prototypes from proof-of-concept to production at scale</li> <li>Evaluate ML system performance against business

Senior Machine Learning Engineer at Phia. Apply via Ashby.