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Key Responsibilities
- LLM Development & Implementation: Work on LLM projects using modern frameworks, implementing prompt engineering strategies, fine-tuning techniques, and production-ready solutions
- Proof of Concepts: Design and execute proof of concepts for new AI functionality, evaluating feasibility and performance
- ML Opportunity Discovery: Help identify new machine learning opportunities across the organization, translating business challenges into technical solutions
- Productization Support: Support LLM/ML projects from experimentation through to production deployment
- Cross-functional Collaboration: Work with engineering, product, and business teams to deliver impactful AI solutions
- Best Practices: Contribute to best practices for LLM/ML monitoring, evaluation, and safety, including implementation of guardrails
Required Qualifications
- LLM Experience: Practical experience with Large Language Model projects, including:
oFine-tuning methodologies (LoRA, QLoRA, full fine-tuning, RLHF, etc.)
oLLM evaluation and monitoring approaches
oImplementation of safety guardrails and content filtering
oFamiliarity with modern LLM frameworks (e.g., LangChain, LlamaIndex, Hugging Face)
OAgentic Experience Or Understanding Of How Agents Work
- ML Foundation: Good understanding and practical experience with core machine learning algorithms including clustering, classification, regression, anomaly detection, and optimization techniques across various data scales
- Project Lifecycle Experience: Ability to work on the complete lifecycle of LLM/ML projects from conception through deployment, maintenance, and optimization
- Data Science Methodology: Solid grasp of the data science workflow including experimental design, hypothesis testing, and statistical methods with strong communication skills for explaining complex technical concepts
- Technical Proficiency: Strong programming skills (Python required) and experience with LLM/ML frameworks and libraries
- Experience with cloud platforms, particularly AWS
- Hands-on experience with Databricks or similar big data platforms
- Familiarity with MLOps practices and tools
- Experience with vector databases and retrieval-augmented generation (RAG) systems
- Experience deploying ML models to production environments
- Experience with model monitoring and observability tools
- Contributions to open-source LLM/ML projects
- Someone who can contribute to LLM initiatives from concept to production
- A collaborative team member who works well within the Data Science CoE
- Strong communication skills to work across technical and business teams
Why Basware?
We’re a purpose-driven company with a global footprint and a collaborative culture. At Basware, you’ll work with passionate professionals, cutting-edge technology, and a shared commitment to innovation and excellence.
In addition, we offer
- Competitive salary and company incentive program
- Lunch and recreational benefits, transferable to dental care or massages
- Occupational and mental health services
- Hobby clubs and gym
- Free on-site parking, also for electric cars
- Bicycle or subsidized commuter ticket benefit
- Employee awards and team social events
- Good learning opportunities, e.g. LinkedIn Learning license
- and more!
If you're excited by the challenge, apply now and help shape the future of Basware.
Please submit your resume and cover letter by clicking the ‘I’m interested’ link.
Our recruitment process will include pre-employment actions such as an enhanced background screening by a third party and reference checks.
Basware. Now it all just happens.
Key Skills
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