[Hiring] Machine Learning Engineer @BairesDev

Role Description

In this role, you'll design and deliver end-to-end ML, NLP, LLM, and agentic AI solutions that solve real business problems. Working with state-of-the-art models, you'll optimize inference and large-scale deployments, making LLMs and Transformers run reliably in production with high quality, strong performance, and controlled costs. The impact is direct: the solutions you design and operate power key products, handling large datasets and demanding requirements across Databricks, MLflow, and AWS environments.

What You'll Do:

• Co-define ML, NLP, and agentic AI solutions with product, engineering, and data stakeholders, translating business objectives into measurable success metrics.
• Build data pipelines and feature engineering workflows for training, evaluation, batch scoring, and online inference using Python, PySpark and Databricks.
• Develop, train, evaluate, and maintain traditional ML models and NLP/LLM solutions including Transformers, embeddings, RAG, and structured outputs.
• Design and implement agent workflows connecting LLMs with tools, APIs, retrieval systems, and business rules, including safety checks and observability.
• Package, deploy, monitor, and retrain models on Databricks/MLflow and AWS, exposing reliable FastAPI services for realtime, batch, and async workloads.

Qualifications

• 7+ years of experience delivering end-to-end machine learning, NLP, LLM, and agentic AI solutions from business problem definition to production deployment.
• Strong NLP, text intelligence, and LLM expertise including tokenization, embeddings, semantic search, RAG, structured outputs, function/tool calling, guardrails, and hallucination mitigation.
• Hands-on experience with traditional ML models including classification, regression, ranking, forecasting, segmentation, anomaly detection, and explainability.
• Experience designing agentic AI workflows integrating LLMs with tools, APIs, and retrieval systems, including multi-step reasoning, memory management, and human-in-the-loop review.
• Strong production ML/MLOps experience with Databricks/MLflow and AWS including model packaging, governance, CI/CD, monitoring, drift detection, and cost optimization.
• Advanced proficiency in English.

Benefits

• 100% remote work (from anywhere).
• Excellent compensation in USD or your local currency if preferred.
• Hardware and software setup for you to work from home.
• Flexible hours: create your own schedule.
• Paid parental leaves, vacations, and holidays.
• Innovative and multicultural work environment: collaborate and learn from the global Top 1% of talent.
• Supportive environment with mentorship, promotions, skill development, and diverse growth opportunities.