About the Role We are looking for a highly experienced Machine Learning Engineer to join our data science team in driving AI/ML innovation across R&D, commercial, and real-world evidence (RWE) functions in a leading pharmaceutical company. You will design, build, and deploy end-to-end ML pipelines that extract insights from complex biological, clinical, and commercial datasets—enabling better treatment decisions, optimizing pricing and forecasting, and accelerating drug development cycles. This is a hands-on role requiring deep technical expertise, cross-functional collaboration, and a strong product mindset. Key Responsibilities Architect and implement ML/AI solutions for use cases such as clinical trial optimization, drug response prediction, demand forecasting, patient adherence modeling, and NLP on medical literature or EHRs. Design scalable pipelines to ingest, clean, model, and deploy models on structured and unstructured healthcare/pharma data using tools such as Python, PyTorch, scikit-learn, HuggingFace, and Airflow. Apply methods such as causal inference, time series forecasting, deep learning, NLP, and anomaly detection to solve business-critical problems in R&D and commercial operations. Build cloud-native solutions in AWS (Sagemaker, Glue, Lambda, Redshift), with some exposure to Azure (Data Factory, Functions) or GCP (BigQuery). Collaborate closely with clinical scientists, biostatisticians, HEOR, commercial analytics, and regulatory teams to align ML solutions with scientific and business goals. Transition ML prototypes to production-ready systems with CI/CD, containerization (Docker), infrastructure-as-code (Terraform), and model tracking (MLFlow). Mentor junior data scientists and support data engineering practices for high-throughput pipelines, data lakes, and reproducible research environments. Participate in code reviews, experimentation best practices, documentation, and agile ceremonies in a collaborative and science-driven environment. Required Skills & Experience 7+ years of experience as a Machine Learning Engineer or Data Scientist, with multiple production-grade ML models deployed at scale. Strong hands-on experience in Python and libraries such as: scikit-learn, PyTorch, HuggingFace, spaCy, pandas, NumPy, FastAPI, and Airflow. Deep knowledge of ML techniques in life sciences: predictive modeling, NLP for biomedical texts, causal inference, demand forecasting, pricing optimization, and patient-level simulations. Fluency with healthcare/pharma data: clinical trial data, EHR, claims, genomic data, drug formulary/market access data, and real-world evidence. Cloud and infrastructure experience: AWS (Sagemaker, Redshift, Glue, Lambda), Azure or GCP a plus. Proficient in SQL, JSON, Parquet, Hive, and tools like MongoDB, ClickHouse, or ElasticSearch. Experience working with visualization and business intelligence tools: Looker, PowerBI, Superset, or Tableau. Track record of mentorship, code quality, and stakeholder collaboration in cross-functional healthcare teams. Preferred Qualifications Experience in a regulated environment (HIPAA, GxP, 21 CFR Part 11). Familiarity with LLM fine-tuning, medical text generation, or biomedical entity extraction. Knowledge of clinical development processes, FDA submission requirements, or pharmacovigilance systems. PhD or MS in a quantitative discipline (e.g., Neuroscience, Computational Biology, Computer Science, Biomedical Engineering). Job Type: Contract Pay: $66.00 - $75.00 per hour Benefits: 401(k) Dental insurance Health insurance Schedule: 8 hour shift Ability to Commute: Bridgewater, NJ 08807 (Required) Ability to Relocate: Bridgewater, NJ 08807: Relocate before starting work (Required) Work Location: In person