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About the role
About Us: At cGxPTech, we are building next-generation AI solutions for the Life Sciences industry, focused on improving efforts in drug discovery and development, data intelligence, clinical insights, and data-driven decision-making. Job Description: We are looking for a skilled Machine Learning Engineer / Data Scientist to design, develop, and deploy AI models for life sciences applications. This role involves working with structured and unstructured data, building predictive models, and integrating AI into real-world products. Responsibilities: - Design, develop, and optimize machine learning models for life sciences use cases. - Work with chemistry manufacturing controls, clinical, regulatory, or business data (structured & unstructured). - Build predictive models (classification, recommendation, NLP). - Develop AI-powered features such as candidate-job matching, resume parsing, or data insights. - Clean, preprocess, and analyze large datasets. - Deploy models using cloud platforms (AWS, Azure, or GCP). - Collaborate with product, engineering, and domain experts. - Ensure data integrity, compliance, and model performance. Requirements: - Bachelor's or Master's in Computer Science, Data Science, Bioinformatics, or related field. - 1 5+ years of experience in Machine Learning/Data Science. - Strong programming skills in Python (NumPy, Pandas, Scikit-learn). - Experience with ML frameworks (TensorFlow, PyTorch, or similar). - Knowledge of NLP techniques (resume parsing, text classification, etc.). - Experience working with APIs and data pipelines. - Familiarity with cloud platforms (AWS/GCP/Azure). Preferred Qualifications: - Experience in Life Sciences / Healthcare / Pharma domain. - Knowledge of GxP, clinical data, or regulatory environments. - Experience with LLMs (OpenAI, Hugging Face, etc.). - Experience in recommendation systems or job matching algorithms. - Exposure to MLOps and model deployment pipelines. What We Offer: - Chance to build AI products in a high-growth Life Sciences startup. - Flexible work environment (Hybrid). - Competitive compensation. - Work on impactful, real-world healthcare and life science solutions. Compensation (Indicative): - Open & As per the experience. - Contract/Freelance options available. How to Apply: Send your resume and portfolio (GitHub/Kaggle/projects) to: . About Us: At cGxPTech, we are building next-generation AI solutions for the Life Sciences industry, focused on improving efforts in drug discovery and development, data intelligence, clinical insights, and data-driven decision-making. Job Description: We are looking for a skilled Machine Learning Engineer / Data Scientist to design, develop, and deploy AI models for life sciences applications. This role involves working with structured and unstructured data, building predictive models, and integrating AI into real-world products. Responsibilities: - Design, develop, and optimize machine learning models for life sciences use cases. - Work with chemistry manufacturing controls, clinical, regulatory, or business data (structured & unstructured). - Build predictive models (classification, recommendation, NLP). - Develop AI-powered features such as candidate-job matching, resume parsing, or data insights. - Clean, preprocess, and analyze large datasets. - Deploy models using cloud platforms (AWS, Azure, or GCP). - Collaborate with product, engineering, and domain experts. - Ensure data integrity, compliance, and model performance. Requirements: - Bachelor's or Master's in Computer Science, Data Science, Bioinformatics, or related field. - 1 5+ years of experience in Machine Learning/Data Science. - Strong programming skills in Python (NumPy, Pandas, Scikit-learn). - Experience with ML frameworks (TensorFlow, PyTorch, or similar). - Knowledge of NLP techniques (resume parsing, text classification, etc.). - Experience working with APIs and data pipelines. - Familiarity with cloud platforms (AWS/GCP/Azure). Preferred Qualifications: - Experience in Life Sciences / Healthcare / Pharma domain. - Knowledge of GxP, clinical data, or regulatory environments. - Experience with LLMs (OpenAI, Hugging Face, etc.). - Experience in recommendation systems or job matching algorithms. - Exposure to MLOps and model deployment pipelines. What We Offer: - Chance to build AI products in a high-growth Life Sciences startup. - Flexible work environment (Hybrid). - Competitive compensation. - Work on impactful, real-world healthcare and life science solutions. Compensation (Indicative): - Open & As per the experience. - Contract/Freelance options available. How to Apply: Send your resume and portfolio (GitHub/Kaggle/projects) to: .