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Machine Learning Assistant Jobs in New York (NOW HIRING)

Kombo

TM Machine Learning 10

New York, NY

Playing an active role in establishing and maturing the RMIT QA Community of Practice. * Assist the QA Manager for Ad Hoc testing duties. Required Experience * Experience in implementing test ...

Kombo

TM Machine Learning 10

New York, NY · On-site

Playing an active role in establishing and maturing the RMIT QA Community of Practice. * Assist the QA Manager for Ad Hoc testing duties. Required Experience * Experience in implementing test ...

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Machine Learning Assistant information

What is a machine learning assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

What are the key skills and qualifications needed to thrive as a machine learning assistant?

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

What are some common challenges a machine learning assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What are the most commonly searched types of Machine Learning jobs in New York?

The most popular types of Machine Learning jobs in New York are:

What are popular job titles related to Machine Learning Assistant jobs in New York?

For Machine Learning Assistant jobs in New York, the most frequently searched job titles are:

What job categories do people searching Machine Learning Assistant jobs in New York look for?

The top searched job categories for Machine Learning Assistant jobs in New York are:

What cities in New York are hiring for Machine Learning Assistant jobs?

Cities in New York with the most Machine Learning Assistant job openings:

Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 23% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Senior Machine Learning Engineer - Enrichment & Content Intelligence

Spotify

New York, NY • On-site

$184K - $262K/yr

Full-time

Medical, Retirement, PTO

Re-posted 23 days ago

Job description

The Experience team designs Spotify's consumer experience-end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints-from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify.

The Enrichment & Content Intelligence team sits within Content Platform in the Experience Mission. We build the metadata-resolution and content-enrichment infrastructure that powers how Spotify understands music and video content at global scale. Our systems help answer foundational questions across the platform: which tracks are the same recording, which music videos match which audio tracks, who wrote and performed a song, and how content relationships connect across Spotify's catalog.

Our infrastructure powers products and experiences used by millions of listeners, artists, and creators every day. From recommendations and charts to royalties and artist tooling, the work we do directly shapes how content is understood and surfaced across Spotify.

We're looking for a Senior Machine Learning Engineer to help evolve the machine learning systems behind Recording Groups, Music Video Resolution, SongDNA, and the Music Knowledge Graph. This role sits at the intersection of multimodal machine learning, entity resolution, and production-scale engineering, with opportunities to work across audio, video, and metadata understanding problems at massive scale.

What You'll Do
  • Own and evolve large-scale ML pipelines powering Spotify's content-resolution systems
  • Lead development of multimodal embedding frameworks supporting multimodal understanding, music video matching, SongDNA
  • Improve entity-resolution systems across music and video content, helping Spotify better understand relationships between recordings, versions, and content formats
  • Design and run experiments to improve precision, recall, and overall content-quality outcomes using offline evaluation, golden datasets, A/B testing, and impact analysis
  • Build scalable ML evaluation and monitoring infrastructure, including standardized datasets, retraining workflows, and continuous improvement systems
  • Contribute to the evolution of the Music Knowledge Graph by improving production ML capabilities, observability, and model lifecycle management
  • Partner closely with Product Managers, Data Scientists, and engineering teams across Content Platform and the wider Experience Mission
  • Help shape technical strategy for the squad and contribute to long-term ML direction across the product area
  • Mentor engineers and contribute to a strong culture of technical collaboration and experimentation
Who You Are
  • You have solid experience building, deploying, and maintaining machine learning systems in production at scale
  • You have strong experience training, evaluating, and operating ML models using modern frameworks such as PyTorch or TensorFlow
  • You have experience working with multimodal machine learning systems across audio, computer vision, text embeddings, or related domains
  • You understand entity resolution, deduplication, record linkage, or large-scale matching problems, ideally across multiple content modalities
  • You know how to design evaluation systems that balance model quality, operational performance, and real-world impact
  • You are experienced working with large-scale distributed data processing systems and ML infrastructure
  • You communicate effectively across engineering, product, and data science stakeholders
  • You are comfortable leading technical initiatives and influencing engineering direction within a team
  • Experience with Scio, Dataflow, Flyte, BigQuery, or similar distributed processing frameworks is a plus
  • Experience with Scala is a plus
  • Experience with computer vision, video understanding, multimodal embeddings, or recommendation systems is a strong plus
Where You'll Be
  • This role is based in New York City
  • We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.
The United States base range for this position is $184,049-262,928 USD, plus equity. The benefits available for this position include health insurance, six-month paid parental leave, 401(k) retirement plan, monthly meal allowance, 23 paid days off, paid flexible holidays, and paid sick leave. These ranges may be modified in the future.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Find our AI notice here: https://lifeatspotify.com/ai-notice
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