Oddr Inc - Machine Learning Engineer

Machine Learning Engineer

About Us :

We are a fast-growing, innovative company at the forefront of leveraging cutting-edge AI and Machine Learning to revolutionize our industry.

We're building intelligent systems that drive significant impact for our customers.

We are looking for a highly skilled and experienced Machine Learning Engineer to join our dynamic team and play a pivotal role in bringing our advanced ML and LLM services to life in production environments.

The Role :

As a Machine Learning Engineer, you will be instrumental in designing, developing, and deploying robust and scalable ML and LLM-powered solutions.

You'll work across the entire ML lifecycle, from ideation and prototyping to production deployment, monitoring, and optimization.

This role requires a deep understanding of modern deep learning techniques, LLM toolchains, and MLOps best practices, with a strong emphasis on productionizing AI services on cloud platforms.

Responsibilities :

• Own the ML / LLM Lifecycle : Lead the end-to-end ownership of Machine Learning and Large Language Model services, from initial design and development through to their successful deployment and operation in production environments.
• Production Deployment : Deploy and manage ML / LLM services on cloud platforms, particularly Azure (AKS, Azure OpenAI, Azure ML), ensuring high availability, performance, and scalability.
• Deep Learning Development : Apply strong Python programming skills and hands-on experience with modern deep-learning stacks such as PyTorch, TensorFlow, or Hugging Face Transformers to build and refine models.
• LLM Toolchain Implementation : Develop features leveraging advanced LLM toolchains, including prompt engineering, function calling / tools, and integration with vector stores (e.g., FAISS, Pinecone).
• Agentic AI Patterns : Implement and refine agentic AI patterns using frameworks like LangChain or LangGraph, including setting up evaluation harnesses and robust guardrails to ensure reliable and controlled LLM behavior.
• Taming Non-determinism : Develop and apply strategies to mitigate LLM non-determinism, ensuring more predictable and consistent outputs from models.
• MLOps & DevOps : Implement and maintain robust MLOps practices, including containerization (Docker), orchestration (Kubernetes), and CI / CD pipelines using Git-based workflows.
• Monitoring & Troubleshooting : Monitor the performance and health of live ML / LLM services, proactively identifying and resolving issues, scaling resources as needed, and troubleshooting complex production problems.
• Collaboration : Work closely with data scientists, product managers, and other engineering teams to translate research and prototypes into production-ready solutions.

Required Qualifications :

Nice-to-Haves :

(ref : hirist.tech)