Senior Machine Learning Engineer

November 20

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Mitratech

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AI • Compliance • SaaS

Mitratech is a leading provider of enterprise legal management, risk management, and human resources solutions. Their platform incorporates automation, analytics, and artificial intelligence technologies to enhance efficiency and compliance across organizations. Mitratech specializes in tools for legal departments, risk management, compliance tracking, and HR management, creating an interconnected environment that empowers professionals to work smarter and achieve better outcomes.

1001 - 5000 employees

📋 Compliance

☁️ SaaS

💰 Private Equity Round on 2017-04

📋 Description

• As a Machine Learning Engineer at Mitratech, you will be assisting in the development of Artificial Intelligence products. • The role will involve analyzing business requirements, understanding the data available, and building models that can solve problems in the legal industry. • 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.

🎯 Requirements

• 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. • 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.). • Good applied statistics skills, such as distributions, statistical testing, regression, etc. • Experience with source code management tools such as Git

🏖️ Benefits

• We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun!