Sr Staff Machine Learning Engineer Jobs in New York
Sr Staff Machine Learning Engineer jobs in New York are among the most competitive and actively recruited positions in the country, concentrated in financial services, media technology, healthcare AI, and enterprise software across New York City, Buffalo, and Albany. Firms like Google, JPMorgan Chase, and IBM maintain significant engineering presences in New York and consistently hire at this senior-staff level. The most sought-after specializations in New York right now are large language model development, MLOps infrastructure, and real-time recommendation systems. Find a role that fits below and apply directly.
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Showing 5 of 22+ Sr Staff Machine Learning Engineer jobs
Team Description:
The Ads Retrieval ML team builds the machine learning systems that identify relevant advertising candidates for Reddit users. Retrieval sits at the heart of the ads delivery funnel: before downstream ranking and auction decisions, our models determine which campaigns and ads are eligible to compete. We work on large-scale retrieval across multiple objectives, placements, and geographies. Our work combines representation learning, candidate generation, nearest-neighbor search, behavioral and contextual signals, and rigorous offline and online experimentation.
Role Description:
We are looking for a Staff Machine Learning Engineer to provide technical leadership for the Retrieval ML team. You will lead the design and evolution of retrieval models and modeling practices that improve relevance, advertiser outcomes, and user experience at Reddit scale. This is an applied ML role centered on retrieval modeling and end-to-end product impact. You will be expected to stay close to the technical details—from data and objective design through model development, evaluation, experimentation, and launch—while setting direction for other engineers.
Responsibilities:
- Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders.
- Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit's advertising surfaces.
- Apply modern approaches such as two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and other deep learning techniques when they create meaningful product value.
- Improve the retrieval stack across key modeling decisions, including objectives, labels, sampling strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.
- Work with approximate nearest-neighbor and vector retrieval systems, reasoning about recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.
- Establish strong evaluation practices that connect retrieval metrics—such as recall, precision, candidate coverage, calibration, and downstream lift—to ads and user outcomes.
- Lead offline analysis and online experiments, interpret ambiguous results, and translate findings into the next modeling iteration.
- Partner with downstream ranking, ads platform, auction, measurement, and product teams to ensure retrieval models integrate effectively into the full ads funnel.
- Write design documents, review code and model changes, and raise the quality bar for modeling, testing, observability, and production ownership.
- Mentor ML engineers and help grow the team's expertise in retrieval, recommendation, and representation learning.
Required Qualifications:
- 7+ years of industry experience, including substantial experience building and shipping applied ML products.
- Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
- Strong understanding of retrieval modeling concepts, including DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
- Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
- Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
- Strong command of experimental design and model evaluation, including how offline retrieval metrics relate to downstream business and user metrics.
- Experience working with large-scale behavioral, contextual, or content datasets and complex feature pipelines.
- Strong software engineering fundamentals and the ability to write clear, reliable, maintainable production code.
- Technical leadership experience: setting direction, leading complex projects, influencing partner teams, and mentoring other engineers.
- Excellent written and verbal communication, with the ability to explain complex modeling choices to technical and non-technical audiences.
Preferred Qualifications:
- Experience with ads retrieval, ad serving, recommendation, search relevance, or marketplace optimization
- Experience modeling user, content, campaign, or ad interactions with sequential, graph, or multimodal signals
- Experience connecting retrieval improvements to downstream ranking, auction, conversion, revenue, or user-experience outcomes
- Experience in ads marketplaces at peer companies
- Publications, patents, or industry contributions in applied ML or ranking systems
- Experience with sequential modeling (e.g., RNNs, Transformers)
Benefits:
- 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-AJ1
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
Team Description:
The Ads Retrieval ML team builds the machine learning systems that identify relevant advertising candidates for Reddit users. Retrieval sits at the heart of the ads delivery funnel: before downstream ranking and auction decisions, our models determine which campaigns and ads are eligible to compete. We work on large-scale retrieval across multiple objectives, placements, and geographies. Our work combines representation learning, candidate generation, nearest-neighbor search, behavioral and contextual signals, and rigorous offline and online experimentation.
Role Description:
We are looking for a Staff Machine Learning Engineer to provide technical leadership for the Retrieval ML team. You will lead the design and evolution of retrieval models and modeling practices that improve relevance, advertiser outcomes, and user experience at Reddit scale. This is an applied ML role centered on retrieval modeling and end-to-end product impact. You will be expected to stay close to the technical details—from data and objective design through model development, evaluation, experimentation, and launch—while setting direction for other engineers.
Responsibilities:
- Define the technical direction and multi-year roadmap for ads retrieval modeling in partnership with engineering, product, data science, and ads stakeholders.
- Design, develop, and launch candidate-generation and retrieval models for campaigns and ads across Reddit's advertising surfaces.
- Apply modern approaches such as two-tower architectures, representation learning, embeddings, sequence models, graph-based methods, and other deep learning techniques when they create meaningful product value.
- Improve the retrieval stack across key modeling decisions, including objectives, labels, sampling strategies, hard-negative mining, feature design, embedding generation, candidate filtering, and retrieval depth.
- Work with approximate nearest-neighbor and vector retrieval systems, reasoning about recall, relevance, freshness, diversity, coverage, latency, and cost trade-offs.
- Establish strong evaluation practices that connect retrieval metrics—such as recall, precision, candidate coverage, calibration, and downstream lift—to ads and user outcomes.
- Lead offline analysis and online experiments, interpret ambiguous results, and translate findings into the next modeling iteration.
- Partner with downstream ranking, ads platform, auction, measurement, and product teams to ensure retrieval models integrate effectively into the full ads funnel.
- Write design documents, review code and model changes, and raise the quality bar for modeling, testing, observability, and production ownership.
- Mentor ML engineers and help grow the team's expertise in retrieval, recommendation, and representation learning.
Required Qualifications:
- 7+ years of industry experience, including substantial experience building and shipping applied ML products.
- Deep experience with information retrieval, candidate generation, recommender systems, ranking, or related relevance problems.
- Strong understanding of retrieval modeling concepts, including DNN, embeddings, two-tower or dual-encoder models, approximate nearest-neighbor search, and multi-stage retrieval.
- Deep experience training, evaluating, debugging, and deploying deep learning models using TensorFlow, PyTorch, or similar frameworks.
- Demonstrated ownership of ML projects from problem framing and data preparation through offline evaluation, online experimentation, production launch, and iteration.
- Strong command of experimental design and model evaluation, including how offline retrieval metrics relate to downstream business and user metrics.
- Experience working with large-scale behavioral, contextual, or content datasets and complex feature pipelines.
- Strong software engineering fundamentals and the ability to write clear, reliable, maintainable production code.
- Technical leadership experience: setting direction, leading complex projects, influencing partner teams, and mentoring other engineers.
- Excellent written and verbal communication, with the ability to explain complex modeling choices to technical and non-technical audiences.
Preferred Qualifications:
- Experience with ads retrieval, ad serving, recommendation, search relevance, or marketplace optimization
- Experience modeling user, content, campaign, or ad interactions with sequential, graph, or multimodal signals
- Experience connecting retrieval improvements to downstream ranking, auction, conversion, revenue, or user-experience outcomes
- Experience in ads marketplaces at peer companies
- Publications, patents, or industry contributions in applied ML or ranking systems
- Experience with sequential modeling (e.g., RNNs, Transformers)
Benefits:
- 100% remote opportunity (we have 4 office locations for hybrid/onsite work preference in NY, SF, LA and Chicago)
- Comprehensive Healthcare Benefits and Income Replacement Programs
- 401k with Employer Match
- Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
- Family Planning Support
- Gender-Affirming Care
- Mental Health & Coaching Benefits
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
#LI-AJ1
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our Candidate Privacy Policy for Potential Employees and Contractors.
Reddit is proud to be an equal opportunity employer, and is committed to building a workforce representative of the diverse communities we serve. Reddit is committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If, due to a disability, you need an accommodation during the interview process, please let your recruiter know.
See All 22 Sr Staff Machine Learning Engineer Jobs in New York
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Find JobsSr Staff Machine Learning Engineer Jobs by City in New York
Where New York roles are concentrated, by current openings.
Sr Staff Machine Learning Engineer Job Market in New York
A snapshot from current New York openings, updated as new roles post.
Who's Hiring
Top Industries Hiring
- Technology & Software
- Insurance
- Consulting & Professional Services
- Retail
- Manufacturing
What New York Employers Look For
The qualifications that appear most often in sr staff machine learning engineer jobs across New York.
- Bachelor's or master's degree in computer science, statistics, or a closely related quantitative field
- Eight or more years of machine learning engineering experience with demonstrated leadership at staff or principal level
- Deep proficiency in Python and at least one major ML framework such as PyTorch or TensorFlow
- Experience designing and deploying large-scale ML systems in cloud environments such as AWS or Google Cloud
- Proven ability to mentor engineers and define technical strategy across cross-functional New York teams
- Familiarity with MLOps practices including model monitoring, CI/CD pipelines, and feature store architecture
Sr Staff Machine Learning Engineer Jobs in New York: Frequently Asked Questions
How do you become a sr staff machine learning engineer in New York?
Reaching the sr staff machine learning engineer level in New York typically requires a strong quantitative degree followed by progressive engineering roles that include technical leadership. New York does not require a state-issued license for this role. Most candidates build toward it by leading ML platform or product projects at a New York employer, earning recognition for cross-team impact, and demonstrating the ability to set engineering direction rather than simply execute on it.
How much do sr staff machine learning engineers make in New York?
Sr staff machine learning engineers in New York earn a median of about $166,180 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $97,430 for the lowest 10% to over $224,590 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire sr staff machine learning engineers in New York?
Employers hiring sr staff machine learning engineers in New York right now include reddit, GEICO, and Radar, based on current listings on Migrate Mate as of September 2026. New York's density of financial institutions, media companies, and enterprise tech firms means demand at this level stays relatively consistent throughout the year compared with other markets.
Which New York cities have the most sr staff machine learning engineer jobs?
New York and Brooklyn account for the largest share of sr staff machine learning engineer openings in New York. New York City drives the majority of demand through its concentration of financial services firms, advertising technology companies, and large tech engineering offices, while secondary markets like Buffalo and Albany reflect the presence of healthcare systems and state government technology initiatives that are expanding applied ML teams.
Are there remote sr staff machine learning engineer jobs in New York?
Yes, and more than most fields. About 83% of sr staff machine learning engineer openings tied to New York are remote or hybrid as of September 2026, reflecting how well the analytical and architectural nature of the role translates to distributed work. The parts of the role most commonly offered fully remote include model design, code review, and cross-functional technical leadership, while on-site expectations tend to cluster around strategic planning cycles or team onboarding periods.
How can I get hired as a sr staff machine learning engineer in New York with little or no experience?
The most realistic entry path is a junior or mid-level machine learning engineer role at a New York employer, using it to build a portfolio of shipped models and measurable impact. Large New York institutions such as Cornell Tech's industry partnerships and NYU's applied ML programs offer project pipelines that connect students to employers. Adjacent roles like data scientist, software engineer on an ML platform team, or ML research associate at a financial services firm in New York frequently serve as the practical on-ramp to senior-track positions.
Where can I find and apply to sr staff machine learning engineer jobs in New York?
You can find and apply to sr staff machine learning engineer jobs in New York on Migrate Mate, which lists current New York openings updated regularly. Find roles that match your experience and seniority level and apply directly to the ones that fit.
See All 22 Sr Staff Machine Learning Engineer Jobs in New York
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