Job Description

This is a Direct Hire positions so please no Corps, w-2 only

4 days/week onsite

Summary:

The Machine Learning Engineer will design, implement, and optimize production-ready ML models, working closely with data scientists and engineers to deliver innovative AI solutions. You will ensure that models are performant, maintainable, and seamlessly integrated with enterprise systems. You will report to the Vice President, Technology Innovation.

The Day-to-Day:

• Build and deploy machine learning models into production environments
• Optimize model training and inference pipelines for performance and scalability
• Collaborate with data engineers to design robust feature pipelines
• Leverage APIs and microservices for integrating AI models into enterprise applications
• Ensure models are explainable, reliable, and compliant with regulatory requirements
• Work with cloud-native ML services (Azure ML, Kubernetes, Docker)
• Research and implement state-of-the-art ML methods for business applications
• Apply NVIDIA NIMs for model optimization and scaling, and use NeMo services for model development and fine-tuning

Your Qualifications:

• 10+ years’ experience developing data-related solutions and software
• 5+ years of experience as an ML Engineer or Software Engineer with ML focus
• 5+ years of proficient experience with Python, strong experience in ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Experience with distributed training and optimization on GPUs (CUDA, RAPIDS)
• Familiarity with data pipelines (Spark, Databricks, Kafka)
• Hands-on experience with CI/CD for ML workflows and container orchestration (Docker, Kubernetes)
• Strong knowledge of algorithms, data structures, and ML system design
• Practical experience deploying on Azure AI services, and use NVIDIA NeMo and NIMs for LLM and generative AI workloads
• Bachelor’s degree in computer science, Machine Learning, or related field

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