Machine Learning Engineer - Remote Work | REF#297365

BairesDev

United States

Remote

CLP 117,763,000 - 176,644,000

Full time

2 hours ago
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Benefits offered by this job

Remote work (100% remote)
USD or local currency salary
Home-office setup provided
Flexible hours
Paid parental leave
Mentorship & growth
Global, multicultural team

Job summary

BairesDev is seeking a Senior Machine Learning Engineer to design, develop, and deploy end-to-end ML/NLP/LLM solutions in a global, remote-friendly setup.

You will work with Databricks, MLflow, PySpark, Python, and AWS to build scalable data pipelines, train models, and serve FastAPI endpoints for real-time and batch workloads, collaborating with product and engineering teams across continents.

Qualifications

  • 7+ years of experience delivering end-to-end machine learning, NLP, LLM, and agentic AI solutions from 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.

Responsibilities

  • 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.

Skills

End-to-end ML delivery
NLP/LLM expertise
Agentic AI concepts
Memory management & optimization

Tools

Python
PySpark
Databricks
MLflow
AWS
FastAPI

Job description

At BairesDev®, we've been leading the way in technology projects for over 15 years. We deliver cutting-edge solutions to giants like Google and the most innovative startups in Silicon Valley.

Our diverse 4,000+ team, composed of the world's Top 1% of tech talent, works remotely on roles that drive significant impact worldwide.

When you apply for this position, you're taking the first step in a process that goes beyond the ordinary. We aim to align your passions and skills with our vacancies, setting you on a path to exceptional career development and success.

Machine Learning Engineer at BairesDev

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.
What We Are Looking For
  • 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.
How we do make your work (and your life) easier:
  • 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 national 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.

Join a global team where your unique talents can truly thrive and make a significant impact!

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