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Machine Learning Engineer
Machine Learning EngineerFanduel • New York, New York, United States
Machine Learning Engineer

Machine Learning Engineer

Fanduel • New York, New York, United States
[job_card.30_days_ago]
[job_preview.job_type]
  • [job_card.full_time]
[job_card.job_description]

THE POSITION

Our roster has an opening with your name on it

We’re looking for a  Machine Learning Engineer  to join our growing team and help design, build, and deploy machine learning systems that power real-world applications. In this role, you’ll work closely with data scientists, engineers, and product managers to bring models from experimentation to production and ensure they perform reliably at scale.

You’ll contribute across the ML lifecycle—including feature engineering, model training, evaluation, deployment, and monitoring—while growing your skills in software development, ML Ops, and scalable infrastructure.

If you’re excited by this challenge and want to work within a dynamic company, then we’d love to hear from you.

In addition to the specific responsibilities outlined above, employees may be required to perform other such duties as assigned by the Company. This ensures operational flexibility and allows the Company to meet evolving business needs.

THE GAME PLAN

Everyone on our team has a part to play

ML Pipeline Development

  • Collaborate with data scientists to implement and optimize machine learning models for production use.
  • Develop and maintain pipelines for data preparation, training, and model deployment.
  • Build tools and services to support real-time and batch inference workloads.

Collaboration & Execution

  • Translate product and business requirements into ML-driven solutions.
  • Participate in agile workflows, including sprint planning, code reviews, and design discussions.
  • Work with engineers and analysts to ensure data integrity and efficient feature computation.
  • Quality & Reliability

  • Implement monitoring and alerting to track model performance and detect issues such as data drift.
  • Write maintainable, testable code and follow best practices in version control and documentation.
  • Help automate training, deployment, and retraining workflows using ML Ops tools.
  • THE ST ACK :   Databricks,   AWS,   Spark, Python,   MLFlow ,   (Generally available ML Libraries) , Terraform,   Github ,   Buildkite

    THE STATS

    What we're looking for in our next teammate

  • 2–4 years of experience in software engineering, machine learning, or data science.
  • Proficiency in Python, with exposure to ML libraries (Scikit-learn, TensorFlow, or   PyTorch ).
  • Solid understanding of data structures, algorithms, and software engineering principles.
  • Hands-on with SQL and comfortable working with large datasets.
  • Familiarity with distributed computing (Apache Spark preferred).
  • Exposure to ML deployment & monitoring practices or strong interest in learning them.
  • Bonus : experience with Databricks,   MLflow , or similar ML Ops tools.
  • Experience with cloud services (AWS preferred, GCP or Azure also valuable).
  • Preferred Qualifications

  • Experience with containerization (Docker, Kubernetes is a plus).
  • Familiarity with orchestration / ML Ops tooling (SageMaker,   MLflow ).
  • Understanding of model evaluation metrics and techniques for improving generalization.
  • Interest in or experience with real-time ML systems, recommendation engines, or NLP.
  • About You

    You might be a great fit if you often ask yourself questions like :

  • "How do complex systems actually work end to end, and how can I make them better?"
  • "What makes software reliable, and how do you design for that from the start?"
  • "Where’s the balance between moving fast and building things that last?"
  • "How do small changes in code or data ripple out into big user or business impacts?"
  • "What can I automate today that will save everyone headaches tomorrow?"
  • "How do different roles   ( engineers, data scientists, product managers , etc.)   fit together to ship something meaningful?"
  • "What skills should I grow next if I want to level up from strong engineer to strong ML engineer?"
  • This role will join our   Personalization team , working directly with senior engineers to :

  • Build and optimize ML pipelines and feedback loops for our flagship recommender system s .
  • Improve observability, monitoring, and on-call reliability across models.
  • Partner with FinOps to optimize Spark jobs and cloud resource usage.
  • Adopt and integrate AI Foundations platform tools into workflows.
  • This person will have mentorship from Staff ICs and the opportunity to grow, directly contributing to the revenue-driving backbone of the company.

    ABOUT FANDUEL

    FanDuel Group is the premier mobile gaming company in the United States and Canada. FanDuel Group consists of a portfolio of leading brands across mobile wagering including : America’s #1 Sportsbook, FanDuel Sportsbook; its leading iGaming platform, FanDuel Casino; the industry’s unquestioned leader in horse racing and advance-deposit wagering, FanDuel Racing; and its daily fantasy sports product.

    In addition, FanDuel Group operates FanDuel TV, its broadly distributed linear cable television network and FanDuel TV+, its leading direct-to-consumer OTT platform. FanDuel Group has a presence across all 50 states, Canada, and Puerto Rico.

    The company is based in New York with US offices in Los Angeles, Atlanta, and Jersey City, as well as global offices in Canada and Scotland. The company’s affiliates have offices worldwide, including in Ireland, Portugal, Romania, and Australia.

    FanDuel Group is a subsidiary of Flutter Entertainment, the world's largest sports betting and gaming operator with a portfolio of globally recognized brands and traded on the New York Stock Exchange (NYSE : FLUT).

    PLAYER BENEFITS

    We treat our team right

    We offer amazing benefits above and beyond the basics. We have an array of health plans to choose from (some as low as $0 per paycheck) that include programs for fertility and family planning, mental health support, and fitness benefits. We offer generous paid time off (PTO & sick leave), annual bonus and long-term incentive opportunities (based on performance), 401k with up to a 5% match, commuter benefits , pet insurance, and more - check out all our benefits here :   FanDuel Total Rewards .

  • Benefits differ across location, role, and level.
  • FanDuel is an equal opportunities employer and we believe, as one of our principles states, "We are One Team!". As such, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, creed, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, or any other characteristic protected by state, local or federal law. We believe FanDuel is strongest and best able to compete if all employees feel valued, respected, and included.

    The applicable salary range for this position is $116,000 - $152,250 USD, which is dependent on a variety of factors including relevant experience, location, business needs and market demand. This role may offer the following benefits : medical, vision, and dental insurance; life insurance; disability insurance; a 401(k) matching program; among other employee benefits. This role may also be eligible for short-term or long-term incentive compensation, including, but not limited to, cash bonuses and stock program participation. This role includes paid personal time off and 14 paid company holidays. FanDuel offers paid sick time in accordance with all applicable state and federal laws.

    FanDuel is committed to providing reasonable accommodations for qualified individuals with disabilities. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please email   Benefits@fanduel.com .

    It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

    #LI-Hybrid

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