Valiance Solutions - Machine Learning Engineer - Data Modeling

Key Responsibilities :

- Design and implement scalable deployment pipelines for open-source Gen AI models (LLMs, diffusion models, etc.)

- Fine-tune and optimize models using techniques like LoRA, quantization, distillation, etc.

- Manage inference workloads, latency optimization, and GPU utilization.

- Build CI/CD pipelines for model training, validation, and deployment.

- Integrate observability, logging, and alerting for model and infrastructure monitoring.

- Automate resource provisioning using Terraform, Helm, or similar tools on GCP/AWS/Azure.

- Ensure model versioning, reproducibility, and rollback using tools like MLflow, DVC, or

Weights & Biases.

- Collaborate with data scientists, backend engineers, and DevOps teams to ensure smooth

production rollouts.

Required Skills & Qualifications :

- 5+ years of total experience in software engineering or cloud infrastructure.

- 3+ years in MLOps with direct experience in deploying large Gen AI models.

- Hands-on experience with open-source models (e.g., LLaMA, Mistral, Stable Diffusion, Falcon,

etc.)

- Strong knowledge of Docker, Kubernetes, and cloud compute orchestration.

- Proficiency in Python and familiarity with model-serving frameworks (e.g., FastAPI, Triton

Inference Server, Hugging Face Accelerate, vLLM).

- Experience with cloud platforms (GCP preferred, AWS or Azure acceptable).

- Familiarity with distributed training, checkpointing, and model parallelism.

Good to Have :

- Experience with low-latency inference systems and token streaming architectures.

- Exposure to LLMOps tools (LangChain, BentoML, Ray Serve, etc.)

Why Join Us :

- Collaborative team with deep expertise in AI, cloud, and enterprise software.

- Flexible work environment with a focus on innovation and impact