Job Description
Our dedicated Data Science team is at the forefront of revolutionizing pharma intelligence and how patients gain access to life-saving therapies. Armed with cutting-edge technology and a passion for innovation, we leverage the vast landscape of data to extract actionable insights that drive informed decision making.
Our unique collaborative approach fosters a dynamic synergy between data science and product development. Our deep expertise in machine learning, artificial intelligence, advanced statistical modelling, and big data, combined with our domain knowledge, enables us to deliver comprehensive solutions that empower our clients to stay ahead in a rapidly evolving industry.
SCOPE OF THE ROLE
In this role as a Senior Machine Learning Engineer you will:
Design and implement data ingestion, model training, validation, deployment and monitoring pipelines across the organization
Optimize ML infrastructure and systems for maintainability, scalability, robustness, efficiency, and operating costs
Collaborate with product stakeholders, data scientists and engineering teams to design and implement AI / ML solutions for complex business problems and use cases
Define reference architectures suitable to answer complex questions, including via code interpreting, LLM tool use and leveraging secondary data science models
Stay up-to-date, constantly learning about advances in the field, and deliver periodic presentations to internal teams on these developments
REQUIREMENTS:
Basic Qualifications
- Graduate degree in Computer Science, Engineering, Statistics or a related quantitative discipline, or equivalent work experience
- 5+ years of experience designing large scale, complex, data intensive, AI / ML applications in an industrial setting
- Substantial depth and breadth in system design, latency optimization, cloud infrastructure optimization, knowledge graphs, and MLOps
- Deep understanding of CS fundamentals, computational complexity and algorithm design
- Experience with building large-scale distributed systems in an agile environment and the ability to build quick prototypes
- Excellent knowledge of Python and core data science libraries including Pandas, NumPy and other similar libraries
- Experience mentoring junior team members
- Excellent problem solving and communication skills
Preferred Qualifications
- Knowledge of the healthcare domain and experience with applying AI to healthcare data
- Experience with AWS especially in relation to ML workflows with SageMaker, ECS, serverless compute and storage such as S3 and Snowflake