Senior AI Engineer

We are looking for a Senior ML Engineer to design and deliver AI and ML systems across varied projects. Current work includes gathering public web information to enrich internal intelligence, developing AI personas for sandbox simulations, and using Databricks for data and ML experiments. You should be comfortable owning ambiguous problems and choosing practical solutions.

Location: Remote from the US, Brazil, or Europe

Time Zone EST

Responsibilities :

• Build modular services and APIs for an internal user interface, with structured responses and evidence links.
• Reuse existing crawler components for approved sources and build scheduled or analyst-triggered batch pipelines for parsing, normalization, deduplication, metadata, and refresh.
• Deliver competitor-event analysis, patient-language search and question answering, and structured reactions to candidate messages grounded in curated evidence.
• Build grounded retrieval and generation that cite sources and distinguish facts, evidence, hypotheses, and launch implications; track prompts, models, outputs, and versions.
• Evaluate retrieval, factual accuracy, citations, consistency, and business usefulness with experts; define human-review checkpoints and release criteria.
• Deploy and support AWS services and workers with secure access, CI/CD, tracing, retries, and monitoring; collaborate across teams through user acceptance testing and stabilization.

What we expect :

• Web Scraping / Data Extraction
• Advanced Python and experience with PyTorch, scikit-learn, or similar ML frameworks; modular, tested REST services using FastAPI, Flask, or comparable frameworks.
• Strong SQL and experience with relational databases such as PostgreSQL, plus vector search with pgvector or a comparable system.
• Production LLM applications with prompts, structured outputs, tool use, RAG, embeddings, metadata filtering, source citations, and evaluation.
• Batch pipelines for web or document extraction, normalization, deduplication, incremental refresh, and workflow orchestration.
• AWS, Docker, CI/CD, logging, tracing, monitoring, and secure deployment, including access controls, secrets, and failure handling.
• Independent architecture and delivery under ambiguity, troubleshooting across application and data layers, and clear collaboration with technical and business stakeholders.

Nice to have :

• Competitive intelligence, market research, pharmaceutical Commercial, or launch planning.
• Event detection, evidence-linked summaries, synthetic personas, and human review of strategic AI outputs.
• Redis or similar caching systems, AWS Step Functions or Airflow, and integration with enterprise UI platforms.

We offer :

• Competitive compensation
• Remote work
• Flexible working hours
• Continuous education, mentoring, and professional development programs
• A team with excellent tech. expertise