Applied Machine Learning Engineer (m/f/d)

• thinkproject

• Pune (IND)

• Fulltime

• Published: 2025-07-17

Key Responsibilities:

• Model Development: Design and implement machine learning models using structured and unstructured historical contract data to support intelligent document search, clause classification, metadata extraction, and contract risk scoring.
• BigQuery ML Integration: Build, train, and deploy ML models directly within BigQuery using SQL and/or Python, leveraging native GCP tools (e.g., Vertex AI, Dataflow, Pub/Sub).
• Data Preprocessing & Feature Engineering: Clean, enrich, and transform raw data (e.g., legal clauses, metadata, audit trails) into model-ready features using scalable and efficient pipelines.
• Model Evaluation & Experimentation: Conduct experiments, model validation, A/B testing, and iterate based on precision, recall, F1-score, RMSE, etc.
• Deployment & Monitoring: Operationalize models in production environments with monitoring, retraining pipelines, and CI/CD best practices for ML (MLOps).
• Collaboration: Work cross-functionally with data engineers, product managers, legal domain experts, and frontend teams to align ML solutions with product needs.

Skills and Experience:

• Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.
• ML Expertise: Strong applied knowledge of supervised and unsupervised learning, classification, regression, clustering, feature engineering, and model evaluation.
• NLP Experience: Hands-on experience working with textual data, especially in NLP use cases like entity extraction, classification, and summarization.
• GCP & BigQuery: Proficiency with Google Cloud Platform, especially BigQuery and BigQuery ML; comfort querying large-scale datasets and integrating with external ML tooling.
• Programming: Proficient in Python and SQL; familiarity with libraries such as Scikit-learn, TensorFlow, PyTorch, Keras.
• MLOps Knowledge: Experience with model deployment, monitoring, versioning, and ML CI/CD best practices.
• Data Engineering Alignment: Comfortable working with data pipelines and tools like Apache Beam, Dataflow, Cloud Composer, and pub/sub systems.
• Version Control: Strong Git skills and experience collaborating in Agile teams.
  
  Preferred Qualifications:
  
• Experience working with contractual or legal text datasets.
• Familiarity with document management systems, annotation tools, or enterprise collaboration platforms.
• Exposure to Vertex AI, LangChain, RAG-based retrieval, or embedding models for Gen AI use cases.
• Comfortable working in a fast-paced, iterative environment with changing priorities.

Please submit your application, including salary expectations and potential date of entry

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