Senior ML Engineer - NLP & LLM, Remote Impact

BairesDev; Venezuela; Remote; VES 107,431,000 - 143,241,000; Full time

Benefits offered by this job

Remote work

USD salary

Home office setup

Flexible hours

Paid parental leave

Vacation & holidays

Mentorship & growth

Job summary

BairesDev is seeking a senior Machine Learning Engineer to design and deliver end-to-end ML, NLP, LLM, and agentic AI solutions. You will work with state-of-the-art models, optimize inference, and deploy at scale in production environments.

You will collaborate with product, engineering, and data teams to translate business objectives into measurable outcomes, building pipelines, evaluating models, and ensuring cost-effective operations across Databricks and AWS.

Qualifications

• 7+ years delivering end-to-end ML, NLP, LLM, and agentic AI solutions.
• Strong NLP, text intelligence, and LLM expertise including tokenization, embeddings, semantic search, RAG, structured outputs, function/tool calling, guardrails, and hallucination mitigation.

Responsibilities

• Co-define ML, NLP, and agentic AI solutions with product, engineering, and data stakeholders.
• 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.

Skills

Python

PySpark

NLP

LLM

Agentic AI

MLOps

Databricks

AWS

English proficiency

Tools

Databricks

MLflow

AWS

Job description

BairesDev is seeking a senior Machine Learning Engineer to design and deliver end-to-end ML, NLP, LLM, and agentic AI solutions. You will work with state-of-the-art models, optimize inference, and deploy at scale in production environments.

You will collaborate with product, engineering, and data teams to translate business objectives into measurable outcomes, building pipelines, evaluating models, and ensuring cost-effective operations across Databricks and AWS.