Senior AI Python Engineer

About the Role
We are looking for a Senior AI Python Engineer to lead the design, development, and deployment of intelligent systems that solve complex business problems. You will bridge the gap between research and production — building scalable AI pipelines, integrating large language models (LLMs), and mentoring junior engineers. If you are passionate about writing clean, efficient Python code and turning cutting‑edge AI research into reliable products, we want to hear from you.

Key Responsibilities
Design & Develop – Architect and implement production‑ready AI services, including data preprocessing, model training, inference pipelines, and APIs.
Model Lifecycle Management – Lead end‑to‑end model development: from prototyping (Jupyter/notebooks) to versioning, testing, deployment, and monitoring (MLOps).
LLM & Generative AI – Integrate and fine‑tune LLMs (e.g., GPT, Llama, Mistral) for tasks like RAG, summarization, classification, and agents.
Performance Optimisation – Profile and optimise Python code, model inference latency, and memory usage (e.g., using ONNX, TensorRT, vLLM).
Data Engineering – Work with large‑scale datasets: cleaning, feature engineering, and building efficient data loaders (Pandas, Polars, Spark, Dask).
Collaboration – Partner with data scientists, ML researchers, and product managers to translate requirements into robust technical solutions.
Mentorship – Guide and review code for junior engineers, promote best practices (testing, CI/CD, documentation), and contribute to technical roadmaps.
Production Ownership – Deploy and maintain models on cloud infrastructure (AWS/GCP/Azure) using containers (Docker, Kubernetes) and serverless architectures.

Required Qualifications
5+ years of professional Python development experience, with at least 3 years focused on AI/ML applications.
Strong understanding of machine learning fundamentals (supervised/unsupervised, evaluation metrics, overfitting, cross‑validation).
Deep experience with Python AI/ML stack:
Frameworks: PyTorch, TensorFlow, or JAX
Libraries: scikit‑learn, transformers (Hugging Face), LangChain, LlamaIndex
Data: NumPy, Pandas, Polars, SQL
Proven experience deploying models to production (e.g., FastAPI, Flask, Ray Serve, TorchServe, or BentoML).
Solid grasp of software engineering best practices:
Version control (Git), unit testing, integration testing
Code reviews, CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins)
Docker, Kubernetes (or similar orchestration)
Experience with cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML) and MLOps tools (MLflow, Weights & Biases, Kubeflow, TFX).
Strong problem‑solving and communication skills – you can explain technical trade‑offs to non‑engineers.

Nice‑to‑Have
Experience with LLM fine‑tuning (LoRA, QLoRA, PEFT) and quantization (GPTQ, AWQ).
Knowledge of vector databases (Pinecone, Weaviate, Milvus, pgvector).
Contributions to open‑source AI projects or research papers.
Experience with real‑time inference (WebSockets, gRPC, Kafka) or edge deployment (ONNX Runtime, TF Lite).
Familiarity with prompt engineering, agent frameworks (AutoGen, CrewAI), or RAG evaluation (Ragas).
Background in computer vision, NLP, or time‑series forecasting is a plus.

What We Offer
Competitive salary + equity / bonus package
Flexible working hours and remote‑first culture
Learning budget for conferences, courses, and certifications
High‑performance computing resources (GPUs, cloud credits)
Opportunity to work on cutting‑edge AI products with real impact
Clear career growth path (Principal Engineer / AI Architect)

How to Apply
Send your resume and a brief note explaining your most impactful AI Python project to [email protected] with subject starting from "HELLO_DEVORA21", also click “Apply Now” below. Include links to GitHub, Kaggle, or published work if available