Bounteous - Machine Learning Engineer

Job Description :

You will design, build, and deploy production-grade machine learning systems that solve real business challenges.

Working closely with cross-functional teams, you'll transform innovative ideas into scalable AI solutions.

Core Responsibilities :

- Architect and implement end-to-end machine learning solutions, from proof of concept to production deployment.

- Design and develop ML pipelines using modern frameworks (TensorFlow, PyTorch, scikit-learn) for applications in NLP, computer vision, and predictive analytics.

- Lead the integration of Large Language Models (Vertex AI Gemini, GPT-4) into production systems, including prompt engineering and response optimization.

- Build robust MLOps infrastructure for model monitoring, versioning, and automated retraining.

- Collaborate with product teams to translate business requirements into technical specifications.

Technical Requirements :

- Strong software engineering foundation with production-level Python experience.

- Expertise in ML frameworks : TensorFlow/PyTorch, scikit-learn, and modern ML libraries.

- Proven experience with ML infrastructure and deployment :

1. Model serving and scalability.

2. Containerization (Docker) and orchestration (Kubernetes).

3. CI/CD pipelines for ML workflows.

4. Cloud platforms (AWS/Azure/GCP).

- Proficiency in data processing and analysis.

- Data preprocessing and feature engineering.

- Performance optimization and debugging.

- Big data technologies (Spark, distributed computing).

- Experience with LLM integration and optimization

- Prompt engineering and chain-of-thought implementations.

- RAG (Retrieval Augmented Generation) architectures.

- Vector databases and semantic search.

MLOps & Best Practices :

- Experience with ML monitoring and observability tools.

- Understanding of A/B testing and experimentation frameworks.

- Knowledge of model versioning and reproducibility.

- Familiarity with ML security and ethical considerations.

Ideal Background :

- Bachelor's/Master's in Computer Science, Engineering, or related field.

- 5+ years of software engineering experience.

- Strong track record of deploying ML systems to production.

- Experience mentoring junior engineers and contributing to technical discussions.

What Sets You Apart :

- Open-source contributions to ML/AI projects.

- Experience with distributed training and model optimization.

- Publication record in ML/AI conferences or journals.

- Domain expertise in NLP, computer vision, or recommendation systems.