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Urgent! Lead/ Senior Python Developer + Data Scientist_ Exp: 8+years Jobs | Atyeti Inc

Lead/ Senior Python Developer + Data Scientist_ Exp: 8+years



Job description

Responsibilities

  • AI/ML & LLM Expertise:
  • Design, fine-tune, and deploy small and open-source large language models (LLMs) such as Llama, Mistral, OpenAI GPT, etc.

  • Hands-on leadership in prompt engineering, few-shot prompting, and building advanced NLP/NLU workflows.

  • Guide adoption of modern AI/ML frameworks (Hugging Face Transformers, LangChain, LangGraph, etc.) and architect reusable pipelines in Python.

  • Python & API Development:
  • Drive critical systems architecture in Python, using best practices in API and microservices design (FastAPI, Flask, Django, etc.).

  • Cloud Deployment (AWS/Azure/GCP):
  • Architect, deploy, and scale robust, production-grade ML/AI solutions on cloud (AWS strongly preferred), leveraging cloud-native tools (Lambda, S3, ECS/ECR/Fargate, etc.), serverless, and IaC (CloudFormation/Terraform).

  • Champion DevOps best practices, automation, containerization (Docker/K8s), CI/CD, and operational monitoring.

  • Technical Leadership:
  • Mentor engineers, lead by example, drive system architecture reviews and code standards, and ensure high-quality technical delivery across teams.

  • Act as the technical point of contact for escalation, incident resolution, and production troubleshooting.

Requirements

  • Experience:
  • 8+ years in software development, including 3+ in senior or lead roles delivering ML/AI solutions in a cloud environment.

  • LLM & Prompt Engineering:
  • Strong real-world experience in LLM prompt engineering, few-shot prompting, and fine-tuning (using frameworks like Hugging Face, LangChain, LangGraph, etc.).

  • Python Expertise:
  • Mastery of Python for API/microservice development, object-oriented patterns, code optimization, automated testing, and packaging.

  • Cloud (AWS Preferred):
  • Hands-on deployment and scaling of AI/ML services on AWS, Azure, or GCP; proficient in containers, serverless, and infrastructure as code.

  • Technical Leadership:
  • Proven experience mentoring software engineers, shaping system design, and driving cross-team initiatives.

  • Communication:
  • Exceptional ability to explain complex technical subjects and influence technical direction with diverse audiences.

Nice to Have

  • Databricks:
  • Experience building, deploying, or orchestrating ML/AI or data pipelines on Databricks (Data Engineering, MLflow, collaborative workflows, jobs).

  • (Note: Knowledge of Databricks is highly valued but not required ; candidates without PySpark but with Databricks experience are welcome.)
  • PySpark:
  • Experience using PySpark for big data ETL/processing, but not a must-have .

  • Data Engineering:
  • Familiarity with Spark, Airflow, advanced data analytics stacks, and modern data lakes (e.g., Delta Lake).

  • ML Productionization & MLOps:
  • Experience with ML lifecycle tools, CI/CD pipelines, monitoring, and model governance.

  • Visualization:
  • Python-based dashboarding/analytics (Streamlit, Dash, Plotly).

  • Security & Compliance:
  • Secure cloud design, IAM, encryption, and compliance frameworks.

  • Published Work / Open Source:
  • Contributions to AI/ML communities, conference presentations, or technical publications.


Required Skill Profession

Other General



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