Staff AI/ML Engineer

$175,800 - $201,000/Yr

Ancestry - Lehi, UT

posted 2 months ago

Full-time - Mid Level
Hybrid - Lehi, UT
Professional, Scientific, and Technical Services

About the position

As a Staff AI/ML Engineer at AncestryDNA, you will play a pivotal role in leading a technological transformation that shapes the future of how we utilize data and machine learning to extract insights from DNA data. This position does not require prior experience with DNA, making it accessible to a broader range of candidates. Your primary responsibility will be to design and implement scalable machine learning models and AI solutions that leverage AWS big data technologies. You will collaborate closely with cross-functional teams, including ML scientists, computational biologists, and software developers, to understand project requirements and deliver high-impact AI/ML solutions that meet the needs of our customers. In this role, you will optimize data processing and machine learning workflows on AWS, focusing on efficiency, security, and responsible AI practices. You will drive the adoption of best practices in code, architecture, and processes across the team, ensuring that all projects align with business objectives. As a technical leader, you will provide guidance in ML project planning and execution, mentor junior engineers and data scientists, and promote a culture of learning and innovation within the team. Staying updated with the latest developments in AWS services, machine learning, and AI technologies will be crucial for driving continuous improvement in our processes and solutions. You will manage multiple projects simultaneously, adjusting priorities as needed to meet deadlines. Your experience and insights will be invaluable as you contribute to a team that is dedicated to excellence in a fast-paced and continuously evolving environment, leveraging the planet's largest genetic database to enrich the lives of our customers.

Responsibilities

  • Design and implement scalable machine learning models and AI solutions leveraging AWS big data technologies.
  • Collaborate with cross-functional teams including ML scientists, computational biologists, and software developers to understand project requirements and deliver high-impact AI/ML solutions.
  • Optimize data processing and machine learning workflows on AWS, focusing on efficiency, security, and responsible AI.
  • Drive the adoption of best practices in code, architecture, and processes across the team.
  • Provide technical leadership in ML project planning and execution, ensuring alignment with business objectives.
  • Mentor junior engineers and data scientists, promoting a culture of learning and innovation.
  • Stay updated with the latest developments in AWS services, machine learning, and AI technologies to drive continuous improvement.
  • Manage multiple projects simultaneously, adjusting priorities as needed to meet deadlines.

Requirements

  • Minimum of 5 years of experience in machine learning, data science, or a related field, with a proven track record of deploying scalable AI/ML solutions.
  • Experience with Infrastructure as Code (IaC), ideally Terraform.
  • Extensive experience with AWS cloud services such as Amazon S3, EC2, EMR, RDS, Redshift, SageMaker, and AWS Lambda.
  • Proficient in big data technologies and tools like Apache Hadoop, Spark, and Kafka.
  • Strong programming skills in Python and/or other programming languages.
  • Experience with ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras.
  • Excellent problem-solving, organizational, and communication skills.
  • Demonstrated ability to work in a fast-paced and highly collaborative environment.

Nice-to-haves

  • Experience with data visualization tools and techniques.
  • Familiarity with genetic data analysis and bioinformatics.
  • Knowledge of data governance and compliance standards.

Benefits

  • Health insurance coverage
  • Dental insurance coverage
  • Vision insurance coverage
  • 401(k) retirement savings plan
  • Bonus eligibility
  • Equity options
  • Flexible work location options (remote, hybrid, or in-office)
  • Paid time off and holidays
  • Professional development opportunities
  • Employee discounts on products and services
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