Machine Learning Engineering Manager, Recommendations Job at Suno (San Francisco)

Senior Machine Learning Engineering Manager

Atlassian is looking for a Senior Machine Learning Engineering Manager to join o...

Location

United States , Seattle; Austin; New York; Washington DC

Salary:

190300.00 - 305600.00 USD / Year

Atlassian

Expiration Date

Until further notice

Requirements

Master or PhD in a quantitative subject (Computer Science, Mathematics, Statistics, Operations Research, or relevant work experience)
5+ years of experience managing machine learning engineering teams running core services at scale
Experience building and scaling machine learning models in business applications using large amounts of data
Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story
Focus on business practicality and the 80/20 rule
very high bar for output quality, but recognize the business benefit of 'having something now' vs 'perfection sometime in the future'
Agile development mindset, appreciating the benefit of constant iteration and improvement

Job Responsibility

Manage the end-to-end machine learning lifecycle, from data collection and preprocessing, to model development and deployment, to evaluation and monitoring
Research and implement novel machine learning techniques and algorithms that can improve the performance, scalability, and robustness of our Recommendation system, and other AI/ML models
Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation
Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence
Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders

What we offer

health coverage
paid volunteer days
wellness resources

Fulltime

Senior Machine Learning Engineering Manager

The GenAI foundation and quality team works cross-functionally, providing genera...

Location

Australia , Sydney

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Master or PhD in a quantitative subject (Computer Science, Mathematics, Statistics, Operations Research, or relevant work experience)
5+ years of experience managing machine learning engineering teams running core services at scale
Experience building and scaling machine learning models in business applications using large amounts of data
Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story
Focus on business practicality and the 80/20 rule
very high bar for output quality, but recognize the business benefit of 'having something now' vs 'perfection sometime in the future'
Agile development mindset, appreciating the benefit of constant iteration and improvement

Job Responsibility

Manage the end-to-end machine learning lifecycle, from data collection and preprocessing, to model development and deployment, to evaluation and monitoring
Research and implement novel machine learning techniques and algorithms that can improve the performance, scalability, and robustness of our Recommendation system, and other AI/ML models
Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation
Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence
Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders

What we offer

Health and wellbeing resources
Paid volunteer days
Wide range of perks and benefits to support family and personal goals

Fulltime

Senior Machine Learning Engineering Manager

The GenAI foundation and quality team sits within the Search and AI Conversation...

Location

United States , Seattle; Mountain View

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Master or PhD in a quantitative subject (Computer Science, Mathematics, Statistics, Operations Research, or relevant work experience)
5+ years of experience managing machine learning engineering teams running core services at scale
Experience building and scaling machine learning models in business applications using large amounts of data
Ability to communicate and explain data science concepts to diverse audiences, craft a compelling story
Focus on business practicality and the 80/20 rule
very high bar for output quality, but recognize the business benefit of 'having something now' vs 'perfection sometime in the future'
Agile development mindset, appreciating the benefit of constant iteration and improvement

Job Responsibility

Manage the end-to-end machine learning lifecycle, from data collection and preprocessing, to model development and deployment, to evaluation and monitoring
Research and implement novel machine learning techniques and algorithms that can improve the performance, scalability, and robustness of our Recommendation system, and other AI/ML models
Mentor and coach your team members on best practices, code quality, design patterns, testing, debugging, and documentation
Hire, onboard, and retain top talent for your team and foster a culture of innovation, collaboration, and excellence
Communicate effectively with internal and external partners, present technical concepts and results clearly and concisely, and solicit feedback and input from various stakeholders

What we offer

Health and wellbeing resources
paid volunteer days
various perks and benefits to support you, your family, and engage with your local community

AI and Machine Learning Engineer

This role involves designing, developing, and optimizing AI and machine learning...

Location

United States , Spring

Salary:

79700.00 - 183200.00 USD / Year

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

Bachelor's degree in computer science, engineering, data science, machine learning, artificial intelligence, or closely related quantitative discipline
0-2 years’ experience
Proficiency in programming languages such as Python, R, or Java
Knowledge of libraries and frameworks commonly used in AI and machine learning, such as TensorFlow, PyTorch, or scikit-learn
A solid understanding of statistics, probability, linear algebra, calculus, and optimization methods
In-depth knowledge of machine learning algorithms, techniques, and concepts
Proficiency in working with large datasets, data pre-processing, data cleaning, and exploratory data analysis
Experience with SQL and databases and data visualization tools like Matplotlib or Tableau

Job Responsibility

Designs, develops and implements AI and machine learning models
Gathers and analyzes relevant data sets to train and test machine learning (ML) models
Optimizes algorithms and models to improve their performance
Works closely with cross-functional teams, including data scientists, software engineers, product managers, and domain experts
Keeps accurate and up-to-date AI and machine learning project documentation
Prepares reports and presents findings or recommendations to stakeholders
Participates in regular design review sessions with the engineering manager, team leader, and other stakeholders
Actively seeks and incorporates feedback from the engineering manager or team leader
Attends daily or weekly stand-up meetings
Prepares and delivers detailed presentations and reports to stakeholders

What we offer

Comprehensive health & wellbeing benefits
Investment in personal & professional development
Inclusive work environment celebrating individual uniqueness
Flexibility to manage work and personal needs

Fulltime

Senior Machine Learning Engineer

Providing the right track at the right moment for our users, notify to them the ...

Location

France , Paris

Salary:

Not provided

Deezer

Expiration Date

Until further notice

Requirements

At least 5 years of work experience in machine learning and models deployed in production
Fluent in at least one language in Python, Scala or Java
Already worked on a recommendation engine
Ability to take initiative, strong business sense and and innovative mindset
Fluent in English or French.

Job Responsibility

Look into the data, propose some Machine learning models and experiment to provide a technical solution to the product manager requirements
Code, deploy and monitor Machine learning models in production
Iterate on existing models to improve KPIs
Explore scientific literature, implement papers, design POC to explore innovative solutions to our users problems
Collaborate with our Research team on research project to build the future of the recommendation engine

What we offer

A Deezer premium family account for free
Access to gym classes
Deezer parties several times a year and drinks every thursday
Mental health and well-being support from Moka.Care
Allowance for sports, travelling and culture
Meal vouchers
Great offices always located in dynamic and attractive districts
Hybrid remote work policy

Fulltime

Senior Machine Learning Engineer, Personalization and Recommendations

As a Senior Machine Learning Engineer on the Personalization & Recommendations t...

Location

United States , San Francisco

Salary:

183360.00 - 248000.00 USD / Year

EdTech Jobs

Expiration Date

Until further notice

Requirements

5+ years of experience in applied machine learning or ML-heavy software engineering, with a strong focus on personalization, ranking, or recommendation systems
Demonstrated impact improving key metrics such as CTR, retention, or engagement through recommender or search systems in production
Strong hands-on skills in Python and PyTorch, with expertise in data and feature engineering, distributed training and inference on GPUs, and familiarity with modern MLOps practices — including model registries, feature stores, monitoring, and drift detection
Deep understanding of retrieval and ranking architectures, such as Two-Tower models, deep cross networks, Transformers, or MMoE, and the ability to apply them to real-world problems
Experience with large-scale embedding models and vector search, including FAISS, ScaNN, or similar systems
Proficiency in experiment design and evaluation, connecting offline metrics (AUC, NDCG, calibration) with online A/B test outcomes to drive product decisions
Clear, effective communication, collaborating well with product managers, data scientists, engineers, and cross-functional partners
A growth and mentorship mindset, helping elevate team quality in modeling, experimentation, and reliability
Commitment to responsible and inclusive personalization, ensuring our systems respect learner privacy, fairness, and diverse goals

Job Responsibility

Design and implement personalization models across candidate retrieval, ranking, and post-ranking layers, leveraging user embeddings, contextual signals and content features
Develop scalable retrieval and serving systems using architectures such as Two-Tower models, deep ranking networks, and ANN-based vector search for real-time personalization
Build and maintain model training, evaluation, and deployment pipelines, ensuring reliability, training–serving consistency, observability, and robust monitoring
Partner with Product and Data Science to translate learner objectives (engagement, retention, mastery) into measurable modeling goals and experiment designs
Advance evaluation methodologies, contributing to offline metric design (e.g., NDCG, CTR, calibration) and supporting rigorous A/B testing to measure learner and business impact
Collaborate with platform and infrastructure teams to optimize distributed training, inference latency, and serving cost in production environments
Stay informed on industry and research trends, evaluating opportunities to meaningfully apply them within Quizlet’s ecosystem
Mentor junior and mid-level engineers, supporting technical growth, experimentation rigor, and responsible ML practices
Champion collaboration, inclusion, curiosity, and data-driven problem solving, contributing to a healthy and productive team culture

What we offer

20 vacation days
Competitive health, dental, and vision insurance (100% employee and 75% dependent PPO, Dental, VSP Choice)
Employer-sponsored 401k plan with company match
Access to LinkedIn Learning and other resources to support professional growth
Paid Family Leave, FSA, HSA, Commuter benefits, and Wellness benefits
40 hours of annual paid time off to participate in volunteer programs of choice

Fulltime

Machine Learning Research Engineer

You will be part of Kiddom’s Data Science team, building the foundation of our s...

Location

United States , San Francisco; New York

Salary:

175000.00 - 250000.00 USD / Year

Kiddom

Expiration Date

Until further notice

Requirements

Have 5+ years of industry experience applying machine learning to solve real-world problems with large, complex datasets, with 1–2 years in a technical leadership role
Proven track record designing, evaluating, and deploying ML/AI systems in production environments that drive measurable business impact, ideally in recommendation, personalization, search, or workflow optimization
Strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and common ML toolkits (scikit-learn, XGBoost, TensorFlow/PyTorch)
Strong analytical skills and ability to break down complex problems into measurable hypotheses and experiments
Excellent communication skills with a history of cross-functional collaboration with product, design, and engineering stakeholders

Job Responsibility

Architect and scale machine learning systems for search, personalization, and recommendations that power Kiddom’s teacher helper and insight engine
Develop evaluation-first development workflows to measure how models improve teaching efficiency, lesson planning, and student learning outcomes
Fine-tune machine learning models with feedback signals from teachers and students to align outputs with instructional goals and classroom needs
Design intelligent discovery pipelines that combine semantic retrieval, curriculum alignment, and real-time personalization
Build agentic assistants that help teachers plan lessons, adapt instruction, and reduce repetitive tasks
Collaborate closely with product managers, designers, and curriculum experts to translate high-level educational goals into scalable ML-powered systems
Coach and mentor junior ML engineers and data scientists, fostering technical and professional growth

What we offer

Competitive salary
Meaningful equity
Health insurance benefits: medical (various PPO/HMO/HSA plans), dental, vision, disability and life insurance
One Medical membership (in participating locations)
Flexible vacation time policy (subject to internal approval). Average use 4 weeks off per year
10 paid sick days per year (pro rated depending on start date)
Paid holidays
Paid bereavement leave
Paid family leave after birth/adoption. Minimum of 16 paid weeks for birthing parents, 10 weeks for caretaker parents. Meant to supplement benefits offered by State
Commuter and FSA plans

Fulltime

Learning Process Engineer

This is a career-defining opportunity to play a crucial role in a hyper-scale AI...

Location

United States , Salt Lake City

Salary:

Not provided

PassiveLogic

Expiration Date

Until further notice

Requirements

Technical background in computer science, AI/ML, data engineering, or knowledge systems
Experienced with graph databases (Neo4j, TigerGraph, Weaviate, Neptune), Python/C++, graph query languages (Cypher, Gremlin, GraphQL, SPARQL), graph ML/embeddings, and building ETL pipelines, event-driven systems, and real-time feedback loops
Understanding of feedback-driven model improvement, reinforcement learning, or adaptive systems
Experience working cross-functionally with engineers, designers, and product managers
Analytical mindset: ability to define success metrics, run experiments, and interpret results
Excellent communication skills and a collaborative, problem-solving approach
Background in process engineering, systems design, product operations, or applied AI/ML
Strong systems thinking: ability to model complex workflows and simplify them into actionable processes
Familiarity with human-in-the-loop learning, adaptive systems, or feedback-driven workflows
Proven experience: 5+ years in developing software with an ecosystem nature

Job Responsibility

Architect feedback pipelines: Build and maintain data ingestion and labeling processes that transform user interactions into structured learning signals
Design graph-based knowledge structures: Model, update, and optimize workflows in a graph database (e.g., Neo4j, ArangoDB, Weaviate, or similar)
Implement adaptive logic: Use graph queries and embeddings to inform recommendations, predictions, and workflow adaptation
Integrate human-in-the-loop learning: Deploy mechanisms that incorporate user corrections and contextual feedback into graph representations and model updates
Collaborate with ML and software engineers: Define retraining strategies, model evaluation criteria, and experiment frameworks that leverage graph-based data
Automate performance monitoring: Develop dashboards and metrics for tracking how graph-driven learning impacts system accuracy, adoption, and efficiency

What we offer

Competitive compensation
Generous equity share package
Medical, dental and vision coverage
Disability and life Insurance options
Flex PTO
Team-building events
Free catered lunch in the office Monday — Friday
Free ski pass (We are at the base of Big Cottonwood Canyon)
Free National Park pass
Onsite Gym

Fulltime

Machine Learning Engineering Manager, Recommendations

Suno

Location:
United States , San Francisco

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
January 13, 2026

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