At Mitratech, the business problem is to develop Artificial Intelligence products that simplify operations in the Legal, Risk, Compliance, and HR functions of companies
Requirements
- Familiarity with vector databases, retrieval-augmented generation (RAG), or embedding pipelines.
- Knowledgeable in privacy-preserving ML, federated learning, or reinforcement learning.
- Experience with large-scale models (LLMs, foundation models) or multi-modal AI systems.
- Deep knowledge of ML algorithms, neural networks, and optimization techniques.
- Proficiency in Python and ML libraries (TensorFlow, PyTorch, XGBoost, Scikit-learn).
- Strong understanding of data structures, distributed systems, and cloud platforms (AWS, GCP, OCI, or Azure).
- Experience with ML Ops tools (Docker, Kubernetes, AgentCore, etc.).
Responsibilities
- Model Development: Design, implement, and deploy ML models (e.g., classification, NLP, recommendation, forecasting, computer vision) at scale.
- End-to-End Pipeline Ownership: Build, maintain, and optimize data ingestion, feature engineering, and model training pipelines using frameworks like TensorFlow, PyTorch, or Scikit-learn.
- ML Infrastructure: Assist and improve ML Ops processes (training, testing, deployment, monitoring) using tools such as Kubernetes, MLflow, Airflow, or SageMaker.
- Performance Optimization: Analyze model performance, conduct error analyses, and improve efficiency, latency, and accuracy.
- Collaboration: Partner with cross-functional teams to integrate ML-driven solutions into production systems.
- Leadership & Mentorship: Guide junior engineers and data scientists, set best practices, and help shape the ML engineering roadmap.
Other
- Bachelor’s or Master’s in Computer Science, Machine Learning, Applied Mathematics, or related field
- 5+ years of professional experience in ML system design and deployment.
- We are an equal opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability or veteran status.
