**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]](mailto:[email protected]) with subject
starting from "HELLO_DEVORA21", also click “Apply Now” below. Include links to
GitHub, Kaggle, or published work if available