Blanc Labs is a premier partner for global enterprises, leading the way in digitization, automation, and the development of next-generation digital products and services. Our expertise in digital transformation powers businesses to accelerate service delivery, drive customer engagement, and foster growth.
We are looking for a Senior Machine Learning Engineer to lead the end-to-end development and lifecycle management of machine learning models powered by proprietary data. This is a highly impactful role at the core of our AI ecosystem, responsible for building scalable, production-grade ML systems that directly power intelligent product features.
You will collaborate closely with Data Scientists, AI Engineers, and Principal AI Engineers to identify opportunities, develop robust models, and ensure seamless integration into production systems.
Key Responsibilities
- Design, build, and deploy end-to-end machine learning models using proprietary datasets
- Own the full ML lifecycle, including data preparation, feature engineering, model training, evaluation, and validation
- Collaborate with Data Scientists to identify and prioritize high-impact ML opportunities
- Work with Principal AI Engineers to ensure models align with system architecture and engineering best practices
- Package and expose trained models as scalable APIs for consumption by AI Engineers and downstream systems
- Build and maintain model pipelines, including versioning, retraining, and continuous improvement workflows
- Monitor model performance in production, ensuring accuracy, reliability, and relevance over time
- Troubleshoot model drift, data quality issues, and performance bottlenecks
Qualifications
- Strong experience in machine learning engineering, with production deployment experience
- Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience with data preprocessing, feature engineering, and model evaluation techniques
- Hands-on experience deploying ML models as APIs or microservices
- Familiarity with MLOps practices, including model versioning, monitoring, and retraining pipelines
- Experience working with large-scale or proprietary datasets
- Strong software engineering fundamentals (testing, scalability, performance optimization)
- Ability to collaborate effectively with cross-functional teams
Nice-to-Have
- Experience with cloud platforms (AWS, GCP, or Azure) and ML services (e.g., SageMaker, Vertex AI)
- Familiarity with containerization and orchestration tools (Docker, Kubernetes)
- Experience with real-time or low-latency ML systems
- Exposure to LLMs or hybrid AI/ML systems
- Experience in building data pipelines (Airflow, Spark, etc.)
Blanc Labs is an equal opportunity employer and is