What are the responsibilities and job description for the AI/ML Engineer - Precision Health position at Sci.bio Recruiting?
Seeking an AI/ML Engineer to join a Precision Health startup in Boston, MA to design, train, and deploy machine learning models powering a digital twin platform for real-time simulations. You’ll build scalable pipelines for omics and clinical data, with a focus on privacy-preserving and federated learning.
Responsibilities
Responsibilities
- Build, train, and evaluate ML models for multi-omics and clinical data integration.
- Develop scalable data and model pipelines, including data cleaning, transformation, and orchestration.
- Explore and understand diverse biotech/pharma/healthcare datasets; create informative, appealing data visualizations for stakeholders.
- Work with Data Scientists to perform data cleaning, statistical analysis, and feature engineering; develop pipelines for model selection, training, and evaluation.
- Ensure consistent feature engineering between training and model serving to prevent training-serving skew.
- Implement privacy-preserving ML techniques, including federated learning approaches.
- Partner with data engineering and software teams to deploy models to clinical dashboards; automate model deployment, monitoring, and retraining.
- Adhere to best practices for coding, testing, and designing reusable components.
- Remain flexible across data engineering and machine learning projects based on team backlog and product priorities.
- Evaluate and adopt tools/technologies that improve ETL performance and MLOps efficiency.
- Collaborate effectively in cross-functional teams with data engineers, analysts, and business stakeholders.
- MSc/PhD in Computer Science, AI/ML, or related field.
- 3–6 years of ML engineering experience, ideally in biomedical applications. Experience with Pharmaceutical and Healthcare industry.
- Strong programming skills in Python or R; expertise with libraries for data manipulation, statistical analysis, visualization (charts/plots), and ML algorithms/frameworks.
- Proficiency with Python, TensorFlow, PyTorch, scikit-learn; familiarity with Keras.
- Familiarity with PySpark DataFrames and data processing libraries.
- Experience across the ML lifecycle: feature stores, MLflow, model registry, deployment/serving, and monitoring.
- Outstanding analytical and problem-solving skills; ability to learn quickly; hands-on experience with model selection, training, and evaluation.
- Proficiency in statistical techniques and hypothesis testing; experience with regression, clustering, and classification.
- Fully onsite in Boston, MA.
- Salary: $130k–160k Benefits.
Salary : $130,000 - $160,000