The company is looking to solve complex business challenges for clients across various industries by developing impactful advanced analytics and AI solutions. They aim to help clients stay competitive, transform operations, and achieve lasting improvements through data-driven insights.
Requirements
- SQL and Python’s data-science stack
- Proficiency with Spark/PySpark for distributed workloads.
- Development experience (focus on machine learning)
- GenAI experience a plus: parameter-efficient tuning, RAG architectures, vector-store technologies, LLM evaluation
- Technologies you may encounter include Airflow, Databricks, Dask/RAPIDS, containerization with Docker and Kubernetes, and the major clouds (AWS, GCP, Azure, Oracle)
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 -- using rigorous metrics and A/B tests.
- When appropriate, you’ll build production-grade RAG pipelines and assess LLM output quality / hallucinations
- Deploy models via APIs or batch pipelines, write unit tests, and set up monitoring dashboards to track performance and drift
- 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
- U.S. Citizenship is required
- 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
