Machine Learning Scientist

About Ancestry: When you join Ancestry, you become a part of a human-centered company where every individual's story is valued. Ancestry® is the worldwide leader in family history, fostering personal discovery journeys to enrich lives. Our unique collection of more than 40 billion records, over 3 million subscribers and over 23 million people in our ongoing DNA network, enables customers to uncover their family history and achieve a profound understanding of their lives. Over the previous 40 years, we have built trusted relationships with millions of individuals who have chosen us as their platform for discovering, preserving, and sharing the most significant information about themselves and their families. We support our flexible work location approach, allowing you to decide whether to work in the nearest office, from your home, or a combination of both (subject to location restrictions and roles that require being in the office - see the full list of eligible US locations HERE). We will continue to hire and promote beyond our office locations, fostering expanded opportunities for employee diversity. Together, we strive daily to cultivate an inclusive and diverse work environment where our employees can be themselves. We value every idea and perspective so that our services and products reflect the global and diverse clients we serve. Ancestry encourages applications from minorities, women, disabled individuals, protected veterans, and all other qualified candidates. Are you passionate about dedicating your work to enrich people's lives? Join the curious. AncestryDNA is seeking a motivated and talented Senior Machine Learning (ML) Engineer to join our DNA Science team. Our team is at the cutting edge of developing computational and machine learning methods that connect individuals to their past places and ancestors through genomics. As a Senior ML Engineer, you will collaborate with our enthusiastic team of ML scientists, data scientists, population geneticists, software engineers, and cloud architects to develop and deploy machine learning solutions leveraging the capacities of our AWS ecosystem. You will design, implement, and test innovative algorithmic breakthroughs that will enhance our customers' lives. What You'll Do: - Develop, implement and optimize machine learning algorithms and models using AWS tools and frameworks, such as SageMaker, Lambda, Glue, and more. - Design and implement end-to-end ML pipelines within AWS (SageMaker). - Use AWS infrastructure to train, evaluate, and fine-tune machine learning models at scale, considering factors like model performance, latency, and cost. - Collaborate with engineering teams to deploy and monitor machine learning models in production employing AWS services like SageMaker, ECS, EKS, or Lambda. - Design and build data pipelines that efficiently preprocess, clean, and transform genomics data from various sources, ensuring data quality and consistency. - Collaborate with data engineers to refine data storage solutions, leveraging AWS services such as S3, Redshift, and DynamoDB. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders through presentations, reports, and discussions. Who You Are: - Bachelor's, Master's, or Ph.D. in Computer Science, Bioinformatics, Data Science, or a related field. - Proven experience as a ML Engineer with a focus on AWS services, demonstrated through successful project implementations. - Strong proficiency in ML frameworks such as TensorFlow, PyTorch, scikit-learn, and experience with AWS ML services like SageMaker. - Solid understanding of cloud computing concepts and experience with AWS services such as Lambda, Glue, S3, ECS, EKS, and more. - Experience with genetics, population genetics, population geography, or demography. - Hands-on experience with data preprocessing, feature engineering, model training, and deployment in an AWS environment. - Strong proficiency in programming languages such as Python and Bash. - Experience with containerization technologies (Docker, Kubernetes) and CI/CD pipelines (Harness, Jenkins). - Strong problem-solving skills, attention to detail, and a collaborative mindset. - Excellent communication skills to convey technical concepts to various stakeholders. As a signatory of the ParityPledge in Support of Women and the ParityPledge in Support of People of Color, Ancestry values pay transparency and pay equity. We are pleased to share the base salary range for this position: $104,400 - $154,350 with eligibility for bonus, equity, and comprehensive benefits including health, dental, and vision. The actual salary will vary by geographic region and job experience. We will share detailed compensation data for a specific location during the recruiting process. Read more about our benefits HERE. Additional Information: Ancestry is an Equal Opportunity Employer that makes employment decisions without regard to race, color, religious creed, national origin, ancestry, sex, pregnancy, sexual orientation, gender, gender identity, gender expression, age, mental or physical disability, medical condition, military or veteran status, citizenship, marital status, genetic information, or any other characteristic protected by applicable law. Furthermore, Ancestry will provide reasonable accommodations for qualified individuals with disabilities. All job offers are contingent on a background check that complies with applicable law. For San Francisco office candidates, pursuant to the San Francisco Fair Chance Ordinance, Ancestry will consider for employment qualified applicants with arrest and conviction records. Ancestry is not accepting unsolicited assistance from search firms for this employment opportunity. All resumes submitted by search firms to any employee at Ancestry via-email, the Internet, or in any form and/or method without a valid written search agreement in place for this position will be considered the sole property of Ancestry. No fee will be paid in the event the candidate is hired by Ancestry as a result of the referral or through other means.