Machine Learning Infrastructure/ Platform Engineer
Company: Takeda Pharmaceutical
Location: Springdale
Posted on: September 15, 2023
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Job Description:
By clicking the "Apply" button, I understand that my employment
application process with Takeda will commence and that the
information I provide in my application will be processed in line
with Takeda's Privacy Notice and Terms of Use. I further attest
that all information I submit in my employment application is true
to the best of my knowledge.Job DescriptionAbout 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 fieldSolid
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 practicesPrior 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 VisionFinancial Planning &
Stability: 401(k) with company match and Annual Retirement
Contribution PlanHealth & Wellness programs including onsite flu
shots and health screeningsGenerous time off for vacation and the
option to purchase additional vacation daysCommunity Outreach
Programs and company match of charitable contributionsFamily
Planning SupportFlexible Work PathsTuition reimbursementMore 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 seqThe 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
StatementTakeda 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.LocationsBoston, MAWorker TypeEmployeeWorker
Sub-TypeRegularTime TypeFull time
Keywords: Takeda Pharmaceutical, Penn Hills , Machine Learning Infrastructure/ Platform Engineer, Engineering , Springdale, Pennsylvania
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