Entry Level Machine Learning Engineering Manager Jobs
New grad machine learning engineering manager jobs are open to recent graduates and entry level candidates with zero to two years of experience, where a strong portfolio or internship work can matter more than a long resume. Most openings are on-site roles across Technology & Software, Telecommunications, and Electronics & Hardware, with employers like Pinterest, Qualcomm, and Anthropic hiring at this level now.
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Showing 5 of 7+ Entry Level Machine Learning Engineering Manager jobs
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.
Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.
What you'll do:
- Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
- Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
- Keep up with industry trends in recommendation systems
- Leverage LLMs to enhance content understanding
What we're looking for:
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- Degree in computer science, statistics, or related field; or equivalent experience
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
- Nice to have:
- M.S. or PhD in Machine Learning or related areas
- Publications at top ML conferences
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
- Expertise in scalable realtime systems that process stream data
- Passion for applied ML and the Pinterest product
- Background in computational advertising
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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Our Commitment to Inclusion:
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace the flexibility to do your best work. Creating a career you love? It's Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you'll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won't find anywhere else.
Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads.
What you'll do:
- Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
- Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
- Keep up with industry trends in recommendation systems
- Leverage LLMs to enhance content understanding
What we're looking for:
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- Degree in computer science, statistics, or related field; or equivalent experience
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
- Nice to have:
- M.S. or PhD in Machine Learning or related areas
- Publications at top ML conferences
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
- Expertise in scalable realtime systems that process stream data
- Passion for applied ML and the Pinterest product
- Background in computational advertising
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
#LI-HYBRID
Our Commitment to Inclusion:
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Entry Level Machine Learning Engineering Manager Jobs: Frequently Asked Questions
How do I get an entry level machine learning engineering manager job?
Start by building a portfolio that demonstrates hands-on ML project work, even from coursework, personal projects, or internships. Employers at this level look for familiarity with frameworks like PyTorch or TensorFlow, experience coordinating small technical teams or cross-functional projects, and clear communication of model performance trade-offs. Internship experience leading any part of an ML pipeline gives candidates a measurable edge over applicants with coursework alone.
Which companies hire entry level machine learning engineering managers?
Companies hiring entry level machine learning engineering managers right now include Pinterest, Qualcomm, and Anthropic, based on current listings on Migrate Mate as of November 2026. Hiring at this level tends to come from technology firms, AI-focused startups, and large enterprises building out early-stage ML teams who value growth potential alongside technical foundation.
Are there remote entry level machine learning engineering manager jobs?
Yes, though fully remote postings at this level are less common than for individual contributor roles. About 40% of entry level machine learning engineering manager openings are remote or hybrid as of November 2026, reflecting employer preference for some in-person collaboration during the early management stage. Hybrid arrangements are the most frequently listed flexible option.
Are these new grad machine learning engineering manager jobs?
Yes, many of these postings are new grad and junior-friendly, welcoming recent graduates and candidates with zero to two years of experience. A new grad role at this level typically accepts an internship, a capstone project, or a strong technical portfolio in place of full-time professional history. Look for postings that mention 0 to 2 years required or explicitly welcome entry level applicants.
Which industries hire the most entry level machine learning engineering managers?
Entry Level machine learning engineering manager roles concentrate in Technology & Software, Telecommunications, and Electronics & Hardware, based on current listings on Migrate Mate as of November 2026. These sectors drive early-career hiring because they are actively scaling ML teams and often build structured entry points, such as associate manager tracks, specifically designed to develop junior candidates into full engineering management roles.