Machine Learning Engineer

Requirements

• 4 to 6 years of experience in deploying machine learning systems into production
• Advanced proficiency in Python
• Experience with at least one NLP/LLM project in a production environment
• Hands-on experience with deep learning libraries and frameworks such as PyTorch, Keras, TensorFlow, Fastai, YOLO, etc.
• Strong data engineering skills, including proficiency in SQL, data pipelines, and Pandas
• Excellent communication and collaboration abilities

Nice to Have:

• Familiarity with AWS ML services (e.g., Bedrock, SageMaker)
• Experience with multiple LLMs in production
• Experience in a high-velocity startup environment
• Experience with medical data applications using LLMs and transformer models

Responsibilities

• Develop and implement machine learning models with a focus on NLP and LLM projects
• Collaborate with cross-functional teams to integrate ML solutions into production
• Design and optimize data pipelines to support model training and deployment
• Apply deep learning techniques to extract insights from raw text data
• Ensure scalability and performance of machine learning systems in production

Interview Process

1. First Call (30 mins): Initial meeting with the founders.
2. Take Home Task
3. Second Call (1 hour): Review of the home task and a technical assessment.
4. Decision: Final hiring decision based on overall performance.

Contract Details

• Role: Contract position
• Duration: 6-month contract
• Timezone: London time

Company Details

Helixia is a forward-thinking company dedicated to leveraging machine learning to solve complex problems. We value innovation, collaboration, and excellence in all our projects. Join our team and contribute to pioneering solutions in the AI and ML space.

https://www.helixia.io/

Details

Job-type: Remote - Contract
Budget: ₹300,000 - ₹400,000 per month