Senior Applied Machine Learning Engineer (m/f/d)

Overview

Design, build, and deploy ML models for contract analytics using BigQuery & GCP.

Key Responsibilities

• collaboration
• model evaluation
• bigquery ml
• feature engineering
• model development
• mlops deployment

Tasks

-Collaboration: Work cross-functionally with data engineers, product managers, legal domain experts, and frontend teams to align ML solutions with product needs. -Model Evaluation & Experimentation: Conduct experiments, model validation, A/B testing, and iterate based on precision, recall, F1-score, RMSE, etc. -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 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. -Deployment & Monitoring: Operationalize models in production environments with monitoring, retraining pipelines, and CI/CD best practices for ML (MLOps).

Requirements

• apache beam
• gcp
• bigquery
• python
• mlops
• nlp

What You Bring

-Data Engineering Alignment: Comfortable working with data pipelines and tools like Apache Beam, Dataflow, Cloud Composer, and pub/sub systems. -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. -MLOps Knowledge: Experience with model deployment, monitoring, versioning, and ML CI/CD best practices. -Comfortable working in a fast-paced, iterative environment with changing priorities. -Programming: Proficient in Python and SQL; familiarity with libraries such as Scikit-learn, TensorFlow, PyTorch, Keras. -8+ total years' experience 5+ Years of ML Expertise and Strong applied knowledge of supervised and unsupervised learning, classification, regression, clustering, feature engineering, and model evaluation. -Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field. -GCP & BigQuery: Proficiency with Google Cloud Platform, especially BigQuery and BigQuery ML; comfort querying large-scale datasets and integrating with external ML tooling. -NLP Experience: Hands-on experience working with textual data, especially in NLP use cases like entity extraction, classification, and summarization. -Version Control: Strong Git skills and experience collaborating in Agile teams. -Experience working with contractual or legal text datasets.

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About Thinkproject

-Backed by EQT since 2021. -A standout in 2025: a global partnership with Accenture to accelerate digital adoption in utilities and energy sectors. -Their platform brings together 15+ integrated modules to break data silos and enable a single source of truth.

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