Machine Learning Infrastructure/ Platform Engineer

Company: Takeda
Location: Boston
Posted on: November 20, 2023

Job Description:

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Job Description

About the role:

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on four therapeutic areas and other targeted investments, we push the boundaries of what is possible in order to bring life-changing therapies to patients worldwide.

Join Takeda as a Machine Learning Infrastructure/ Platform Engineer, where you will Build self-service and automated components of a Machine Learning (ML) platform to enable the development and monitoring of machine learning models. You will Design, monitor, and continuously improve ML platform architecture solutions which support applications executing at scale. You will also lead Research existing open-source tools and MLOps and Platform approaches taken by other companies to ensure we are building best-in-class technology.

How you will contribute:

• You will work closely with data scientists, machine learning engineers, data engineers, and other cross-functional teams to ensure the smooth and efficient operation of the infrastructure that drives our business.
• Document best practices, guidelines, and standard operating procedures for the platform and contribute to knowledge sharing within the team.
• As part of our team, you will contribute to the design and development of cutting-edge ML infrastructure and platform to train and serve models at scale, enabling our ML engineers to use the latest techniques in their models.
• Design and implement core ML infrastructure and platform components like Feature Store, Model serving platform and distributed training pipelines.
• Keep up to date with new tools, tech stacks, third-party solutions, and industry trends in ML.
• Collaborate with ML engineers to understand their requirements and identify improvements to our infrastructure and platform.
• Collaborate with leadership to uplevel the ML tech stack and improve the performance of the overall ML ecosystem.
• Build reliable workflows that allow engineers to independently interact with our setup and self-serve the infrastructure they need to run their apps and services.
• Produce system architectures and designs that balance the needs of multiple constituencies and make core scenarios seamless.
• Build and maintain the infrastructure needed to support end-to-end machine learning workflows, including data ingestion, storage, preprocessing, model training, and deployment.
• Scale our ability to reuse models, features, and code in ML systems across the company.
• Champion the interests of internal stakeholders and customers to drive productivity improvements, reduce the time to develop and expand new features. Ensure that their core needs are met to translate models they create into systems operating at scale.
  
  Minimum Requirements/Qualifications:
  
  • Bachelor's or master's degree in computer science, Data Science, or a related field
  • Solid understanding of machine learning concepts and experience working with machine learning frameworks and libraries such as Databricks, Amazon EMR, etc.
  • In-depth understanding of distributed systems, horizontal scaling, caching, microservice architecture and robust system design.
  • Proficiency in programming languages commonly used in machine learning and data applications such as : python, C++, Rust, bash,
  • Prior experience working through the entire lifecycle of ML model: development, training, deployment, experimentation, inference, optimization.
  • Experience with cloud-based services; AWS preferred (e.g., EKS, Lambda, Sagemaker).
  • Experience with containerization and container orchestration technologies (e.g., Docker, Kubernetes, Airflow) and their application to machine learning workflows.
  • Familiarity with CI/CD pipelines for automated model training and deployment.
  • Familiarity with data storage solutions and database technologies commonly used in machine learning and data workflows.
  • Basic understanding of DevOps principles and practices
  • Prior experience building AI infrastructure components like Feature store, training pipeline, model serving.
  • Strong problem-solving and analytical skills, with the ability to quickly identify and resolve platform-related issues.
  • Excellent written and oral communication and collaboration skills to work effectively with cross-functional teams.
  • Basic experience with deep learning tech-stack: TensorFlow and Python.
  • Experience working with computational scientists and understanding their diverse needs.
  • Proficiency developing production grade software incorporating testing and monitoring.
  • Experience with DevOps practices and CI/CD tools (e.g., Git, GitHub Actions).
  • Familiarity with infrastructure as code (IAC) technologies and automated infrastructure management/deployment patterns (e.g., Terraform, Ansible, Helm)
    
    What Takeda can offer you:
    
    
    • Comprehensive Healthcare: Medical, Dental, and Vision
    • Financial Planning & Stability: 401(k) with company match and Annual Retirement Contribution Plan
    • Health & Wellness programs including onsite flu shots and health screenings
    • Generous time off for vacation and the option to purchase additional vacation days
    • Community Outreach Programs and company match of charitable contributions
    • Family Planning Support
    • Flexible Work Paths
    • Tuition reimbursement
      
      More about us:
      
      At Takeda, we are transforming patient care through the development of novel specialty pharmaceuticals and best in class patient support programs. Takeda is a patient-focused company that will inspire and empower you to grow through life-changing work.
      
      Certified as a Global Top Employer, Takeda offers stimulating careers, encourages innovation, and strives for excellence in everything we do. We foster an inclusive, collaborative workplace, in which our teams are united by an unwavering commitment to deliver Better Health and a Brighter Future to people around the world.
      
      This position is currently classified as "remote" in accordance with Takeda's Hybrid and Remote Work policy.
      
      Base Salary Range: $ 130,000 to $ 186,000, based on candidate professional experience level. Employees may also be eligible for Short-term and Long-Term Incentive benefits as well. Employees are eligible to participate in Medical, Dental, Vision, Life Insurance, 401(k), Charitable Contribution Match, Holidays, Personal Days & Vacation, Tuition Reimbursement Program and Paid Volunteer Time Off. This posting is made in compliance with Colorado's Equal Pay for Equal Work Act, C.R.S. - 8-5-101 et seq
      
      The final salary offered for this position may take into account a number of factors including, but not limited to, location, skills, education, and experience.
      
      EEO Statement
      
      Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.
      
      Locations
      
      Boston, MA
      
      Worker Type
      
      Employee
      
      Worker Sub-Type
      
      Regular
      
      Time Type
      
      Full time

Keywords: Takeda, Boston , Machine Learning Infrastructure/ Platform Engineer, Engineering , Boston, Massachusetts