Senior Data/ML Engineer in Brazil, Indiana at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data/ML Engineer based in Brazil.
This role sits at the intersection of data engineering, machine learning, and modern AI systems, focusing on building end-to-end data platforms that power analytics, LLM-driven applications, and intelligent BI solutions. You will be responsible for designing scalable data pipelines and architectures that enable high-quality data flow across warehouses, feature stores, and real-time inference systems. The position requires strong expertise in both traditional data engineering and emerging LLM/AI paradigms, including retrieval-augmented generation and vector-based search systems. You will collaborate closely with BI, data science, and business stakeholders to translate complex requirements into robust and scalable solutions. A key part of your work will involve enabling AI-powered insights, semantic search, and advanced analytics capabilities across the organization. This is a highly technical and innovative environment where engineering excellence and continuous learning are essential to success.
- Design, build, and maintain scalable end-to-end data pipelines for ingestion, transformation, and delivery across data platforms and ML systems.
- Develop workflows for structured and unstructured data processing, enabling semantic search and advanced retrieval capabilities.
- Architect and implement analytics and BI solutions with AI-driven and natural language query functionalities.
- Define and support prompt engineering strategies, orchestration workflows, and model fine-tuning processes for LLM-based applications.
- Manage and optimize vector databases and indexing strategies for retrieval-augmented generation (RAG) systems.
- Collaborate with BI, engineering, and business teams to translate requirements into scalable data and ML solutions.
- Ensure documentation of data workflows, pipelines, and model deployment processes.
- Stay up to date with advancements in data engineering, MLOps, and LLM ecosystems.
- 8+ years of experience in Data Engineering, including at least 2 years focused on MLOps or ML-driven systems.
- Strong proficiency in Python for data processing, transformation, and large-scale data engineering tasks.
- Deep understanding of vector databases, semantic search, and RAG architectures.
- Experience integrating LLM frameworks into production data workflows (training, fine-tuning, and inference).
- Hands-on experience with cloud platforms such as AWS or Azure, including ML/AI services.
- Strong experience with distributed data processing tools such as Apache Spark, Hadoop, and Kafka.
- Solid knowledge of SQL/PLSQL and data warehouse technologies (Snowflake, Redshift, or similar).
- Experience designing complex data pipelines from multiple sources (APIs, RDBMS, JSON, flat files).
- Strong understanding of software engineering principles and experience working in Agile environments.
- Proficiency with Git and collaborative development workflows.
- Strong communication skills in English (written and spoken).
- Nice to have: experience with LangChain, LlamaIndex, Hugging Face, vector DBs (e.g., DataStax AstraDB), CI/CD for MLOps, and LLM optimization techniques.
- Fully remote work opportunity (LATAM-based).
- Competitive compensation aligned with senior-level expertise.
- Opportunity to work on cutting-edge AI, LLM, and data platform initiatives.
- International, English-speaking engineering environment.
- Exposure to large-scale data systems and advanced AI architectures.
- Flexible work setup with autonomy and ownership of technical solutions.
- Continuous learning and exposure to modern MLOps and AI technologies.