Responsibilities

• 5 years of experience in different Data Science topics (e.g. machine learning, LLM, deep learning)

• Deliver independently Data Science projects, bring an e2e product-oriented mindset

• Engage directly with clients to understand their business objectives and translate them into technical requirements.

• Lead pre-sales technical discussions, demonstrating the value and capabilities of our analytics solutions.

• Collaborate with cross-functional teams to integrate AI/ML solutions into the company's product offerings.

• Provide thought leadership and mentorship within the team, fostering a culture of continuous learning and innovation.

• Stay abreast of industry trends and advancements in AI/ML to ensure our solutions remain cutting-edge.

General qualifications:

• Fluent English speaker with excellent communication skills, comfortable in client-facing roles.

• 5 years of experience in data science or a related field.

• Hands-on experience with LLM projects, machine learning, deep learning.

• Affinity to building product / product-oriented vision

• Domain expertise in any of the following fields is highly preferred: international finance, healthcare, pharma or meteorology.

Technical requirements:

• Strong Python and SQL skills

• Leverage cloud-based data science tools on AWS (SageMaker, Bedrock), Azure, or GCP for scalable model training and deployment

• IDE (e.g.: Jupyter, VSCode)

• Version control Git / BitBucket / AZ DevOps

• Core machine learning libraries (sklearn, LightGBM, torch)

• Traditional ML projects (supervised and unsupervised)

• NLP experience / affinity: Understand concepts of text classification, information extraction

• Generative AI & LLM frameworks - HuggingFace / transformers, OpenAI; proprietary API & open-source models

• Understand concepts of RAG, build & maintain pipeline, understand concepts of pretraining, fine-tuning

Nice to have:

• Databricks / distributed computing / scalable ML

• Familiarity with database systems (SQL, NoSQL)

• ML Lifecycle management (e.g.: MLFlow / wandb)

• Web frameworks (e.g.: Streamlit / FastAPI / Flask)

• Automatization pipelines on cloud (e.g.: Azure Functions, AWS Lambda, Databricks notebook jobs)

• API integration

• Experience with deploying ML models in production environments

• Experience with LangChain / LlamaIndex

• Understanding of LLM Agents, agentic behavior, prompt engineering

• Being able to differentiate what 'needs' LLMs and what can be solved with traditional ML / NLP

Why us?

• Diverse projects: In each assignment there is always something new either on the technical or on the business side that helps you grow.

• Cutting edge technology: You will work with many of the most up-to-date technologies and tools.

• Strong and motivating team: We stress the importance of working together in tight-knit, cohesive teams in which members help each other to reach the common goal.

• Work-life balance: We help you to feel good individually as well, and coordinate work so as it should align with your leisure activities.

• Professional development: There are team gatherings on a regular schedule where colleagues can share their knowledge, and have deep technical discussions.

• Focus on company culture: In addition to our business and professional achievements we are proud of the social bonding in the company, which is based on mutual respect and helping one another.

• Personal mentoring: You will have your own mentor (just like everybody at Hiflylabs) who you can turn to with professional issues as well as with personal ones.