The company is looking to solve complex and pressing challenges across industries by developing impactful advanced analytics and AI solutions, optimizing code, and solving complex business challenges.
Requirements
- Professional experience in applying machine learning and data mining techniques to real problems with copious amounts of data
- Development experience (focus on machine learning): SQL and Python’s data-science stack; proficiency with Spark/PySpark for distributed workloads
- Technologies you may encounter include Airflow, Databricks, Dask/RAPIDS, containerization with Docker and Kubernetes, and the major clouds (AWS, GCP, Azure, Oracle)
- GenAI experience a plus: parameter-efficient tuning, RAG architectures, vector-store technologies, LLM evaluation
- Proficiency with SQL
- Proficiency with Python’s data-science stack
- Experience with Spark/PySpark for distributed workloads
Responsibilities
- Translate business questions into analytical approaches and select the right techniques for each problem
- Conduct exploratory data analysis
- Design, implement, and evaluate models—from traditional machine learning to deep learning to LLMs
- Deploy models via APIs or batch pipelines, write unit tests, and set up monitoring dashboards to track performance and drift
- Document assumptions, communicate results in clear, actionable language, and collaborate with engineers to integrate solutions into user-facing applications
- Build models which are accurate, explainable, and free from bias
- Optimize inference latency and cost through parameter-efficient tuning, quantization, and accelerated serving stacks
Other
- Bachelor’s degree in computer science with 2+ years of professional experience OR Masters or PhD a discipline such as computer science, mathematics, statistics or electrical engineering
- Exceptional time management to meet your responsibilities in a complex and largely autonomous work environment
- Strong communication skills, both verbal and written, in English and local office language(s), with the ability to adjust your style to suit different perspectives and seniority levels
- Willingness to travel
- Continuous learning and apprenticeship culture
