Senior Machine Learning Engineer

Summary

Join our team in developing an LLM-based Customer Support Assistant to improve support team efficiency. This role contributes to creating quality solutions, accelerates AI expertise through collaboration with experienced specialists, and involves implementing engineering best practices. You will contribute to project roadmap decisions, create feasibility prototypes, and design and implement client-focused solutions. This position is located in Lithuania and requires proven Python programming skills, experience in prompt engineering and LLM observability, and familiarity with relevant APIs. The company offers a collaborative and fun work culture with various benefits.

Requirements

• Proven skills in Python programming
• Proven experience in prompt engineering, model fine-tuning, working with embedding models, evaluations and implementing LLM observability best practices
• Experience with commercially available APIs for content generation, embeddings, function calling, fine-tuning, etc., and proficiency in fine-tuning prompts for high-quality outcomes
• High curiosity to stay up to date with the evolution of AI field
• Knowledgeable in Linux and DevOps methodologies, including the use of Git, Jira, and Docker
• Experience working in an Agile environment
• Fluency in both Lithuanian and English languages

Responsibilities

• Contribute to creating quality solutions and products for our clients
• Accelerate your AI expertise by working shoulder-to-shoulder with experienced AI specialists
• Bring engineering best practices to the current team environment
• Contribute to decisions regarding the project roadmap
• Make prototypes that quickly prove the feasibility of solutions
• Design and implement solutions that meet client needs

Preferred Qualifications

Experience in product development, as well as familiarity with related methodologies and mindset, would be considered a plus

Benefits

• A working culture that is high performing, ambitious, collaborative and fun
• Health insurance and a yearly training budget (local and international conferences, language courses), employee-led workshops
• Flexible working hours
• Unlimited WFH (work from home) policy
• Extra vacation days: 2 after working at NFQ for two years and 4 after four years on our team
• Bonus for referrals
• For those who dream of traveling: WFA (work from anywhere) possibilities in NFQ - approved countries
• Office perks and team activities