Title : Machine Learning Engineer
Location : Dallas, TX (Hybrid) Locals Only
Long term Contract
Exp 10+ Only
Technical skills requirements
The candidate must demonstrate proficiency in,
• Strong understanding of machine learning and deep learning concepts
• Proficiency in Python (libraries like TensorFlow, PyTorch) with experience in vector data manipulation
libraries
• Experience with generative AI models (transformers, GANs, VAEs) and various LLM architectures
• Experience with front-end development frameworks (e.g., React, Angular) and UI/UX design principles
• Experience with back-end development frameworks (e.g., Django, Flask) and API development (RESTful or
GraphQL)
• Experience with NLP techniques (text cleaning, pre-processing, text analysis)
• Experience with software engineering principles and best practices (object-oriented programming, design
patterns, testing)
• Familiarity with cloud platforms (AWS, Azure, or GCP)
• Knowledge of containerization technologies (Docker, Kubernetes)
• Experience with data integration tools and techniques (a plus)
• Knowledge of chunking strategies for handling large datasets
• Experience working with RAG applications and their functionalities
• Expertise in LangChain and similar tools (e.g., PromptChain) for prompt engineering and data processing in
RAG applications
• Experience with DevOps principles and tools for continuous integration and delivery (CI/CD)
• Experience with building and integrating with analytical dashboards and reporting tools
Nice-to-have skills
• Experience working with RAG applications
• Experience with cloud-based data warehousing solutions (e.g., BigQuery, Redshift, Snowflake)
• Experience with cloud-based workflow orchestration tools (e.g., Airflow, Prefect)
• Familiarity with Kubernetes (K8S) is a welcome addition
• Google Cloud certification
• Unix or Shell scripting
Qualifications
• B.Tech., M.Tech. or MCA degree from a reputed university
From:
Abhishek,
Heliogic
abhi@heliogic.com
Reply to: abhi@heliogic.com