Data Scientist (AI/LLMs) – Advanced Analytics & MLOps
Key Responsibilities
- Develop LLM-based applications from concept to deployment and monitoring
- Design and implement RAG/LLM pipelines: data ingestion, chunking, embeddings, retrieval, re-ranking, and evaluation
- Build and optimize prompt engineering strategies, workflows, and experiments
- Conduct A/B testing and optimize model performance and cost-efficiency in production
- Manage risks such as bias, hallucinations, and data privacy, ensuring Responsible AI practices
- Collaborate closely with product, engineering, and design teams
- Communicate insights and solutions effectively to technical and non-technical stakeholders
Candidate Profile
Experience & Background
- Minimum 3 years of experience in Data Science / Machine Learning Engineering
- Strong foundation in statistics, machine learning, and SQL
- Hands-on experience developing AI/ML solutions and PoCs
- Experience working in Agile environments (Jira, CI/CD practices)
Technical Skills
- Programming: Expert in Python (Pandas, NumPy, Pydantic, scikit-learn), PySpark (desirable)
- LLMs & Generative AI:
- Prompt engineering, embeddings, evaluation, and optimization
- Knowledge of agent and multi-agent architectures (desirable)
- LLM / RAG Ecosystem: LangChain, LangGraph, FAISS, OpenSearch, or similar Vector DBs
- ML Frameworks (Desirable): PyTorch, TensorFlow, Hugging Face Transformers
- MLOps / LLMOps:
- Testing, observability, and deployment
- REST APIs using FastAPI, Flask, or similar
- Integration with third-party AI services (e.g., OpenAI)
- Cloud & DevOps (Desirable):
- AWS (SageMaker, Athena, Lambda, Step Functions, API Gateway)
- Docker, Kubernetes / EKS
- Version Control & CI/CD: Git, Jenkins
Soft Skills
- Strong analytical thinking and problem-solving abilities
- Excellent communication and stakeholder management skills
- Proactive mindset with ownership and accountability
- Ability to work collaboratively in cross-functional teams
- Commitment to Responsible AI practices
What We Offer
- Opportunity to work on state-of-the-art AI and LLM technologies
- Build impactful solutions in a fast-evolving AI landscape
- Collaborative, innovative, and high-performance environment
- Continuous learning and growth in MLOps and Generative AI
Data Scientist (AI/LLMs) – Advanced Analytics & MLOps
Key Responsibilities
- Develop LLM-based applications from concept to deployment and monitoring
- Design and implement RAG/LLM pipelines: data ingestion, chunking, embeddings, retrieval, re-ranking, and evaluation
- Build and optimize prompt engineering strategies, workflows, and experiments
- Conduct A/B testing and optimize model performance and cost-efficiency in production
- Manage risks such as bias, hallucinations, and data privacy, ensuring Responsible AI practices
- Collaborate closely with product, engineering, and design teams
- Communicate insights and solutions effectively to technical and non-technical stakeholders
Candidate Profile
Experience & Background
- Minimum 3 years of experience in Data Science / Machine Learning Engineering
- Strong foundation in statistics, machine learning, and SQL
- Hands-on experience developing AI/ML solutions and PoCs
- Experience working in Agile environments (Jira, CI/CD practices)
Technical Skills
- Programming: Expert in Python (Pandas, NumPy, Pydantic, scikit-learn), PySpark (desirable)
- LLMs & Generative AI:
- Prompt engineering, embeddings, evaluation, and optimization
- Knowledge of agent and multi-agent architectures (desirable)
- LLM / RAG Ecosystem: LangChain, LangGraph, FAISS, OpenSearch, or similar Vector DBs
- ML Frameworks (Desirable): PyTorch, TensorFlow, Hugging Face Transformers
- MLOps / LLMOps:
- Testing, observability, and deployment
- REST APIs using FastAPI, Flask, or similar
- Integration with third-party AI services (e.g., OpenAI)
- Cloud & DevOps (Desirable):
- AWS (SageMaker, Athena, Lambda, Step Functions, API Gateway)
- Docker, Kubernetes / EKS
- Version Control & CI/CD: Git, Jenkins
Soft Skills
- Strong analytical thinking and problem-solving abilities
- Excellent communication and stakeholder management skills
- Proactive mindset with ownership and accountability
- Ability to work collaboratively in cross-functional teams
- Commitment to Responsible AI practices
What We Offer
- Opportunity to work on state-of-the-art AI and LLM technologies
- Build impactful solutions in a fast-evolving AI landscape
- Collaborative, innovative, and high-performance environment
- Continuous learning and growth in MLOps and Generative AI
- Equipo
- Evaluador
- Manager
- Agencia
- Cliente
