We are seeking a Senior Machine Learning Engineer with expertise in implementing Python-based data applications in AWS.

You will be responsible for building and deploying CI/CD pipelines for Natural Language Processing and LLM-based applications, ideally using LLM orchestration frameworks. Your experience in the evaluation and monitoring of LLM-based applications will be crucial for the success of our projects.

#LI-DNI

Responsibilities

• Collaborate with internal teams to design and implement Python-based data applications in AWS
• Build and deploy CI/CD pipelines for Natural Language Processing and LLM-based applications
• Evaluate and monitor LLM-based applications for performance and accuracy
• Develop and deploy GenAI applications for language modeling
• Contribute to the design and implementation of MLOps / AIOps for efficient ML model deployment and management
• Utilize SQL for data querying and manipulation
• Stay updated with the latest developments in the field of Machine Learning Engineering

• At least 3 years of experience in Machine Learning Engineering with a strong focus on Python-based data applications in AWS
• Proven track record of building and deploying CI/CD pipelines for Natural Language Processing and LLM-based applications
• Solid understanding and practical experience with MLOps / AIOps for efficient ML model deployment and management
• Proficiency in SQL for data querying and manipulation
• Experience in developing and deploying GenAI applications for language modeling
• Familiarity with LangChain and/or Llama-index for LLM orchestration
• Ability to evaluate and monitor LLM-based applications for performance and accuracy
• Fluency in English language (B2+ or higher) for effective communication within the team and with stakeholders

• Experience in LLM Application Development and Deployment
• Knowledge of LLM Orchestration Frameworks such as Langchain, llama-index, or HuggingFace
• Previous industry experience in Life Sciences & Healthcare

• CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT:
  • Diversity of tasks and projects
  • Assessment center for objective review of competency level
  • Personal development plan
  • Mentoring programs and leadership development
  • Certification and professional development support
  • Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses
  • English courses taught by certified teachers
• CORPORATE BENEFITS:
  • Extra leave days
  • Referral bonuses
• COMPENSATION PACKAGE:
  • Competitive compensation paid in USD
  • Regular salary and performance reviews
• MEDICAL & HEALTHCARE:
  • Private health insurance
  • Well-being events
• WORKING ENVIRONMENT:
  • Recreation areas and kitchens
  • Tea, coffee, and snacks
  • Well-being events
  • Sports equipment and game consoles
  • IT Equipment
  • Microsoft's Software Assurance Home Use Program (HUP)