Offer summary

Qualifications:

Bachelor's or Master's degree in Computer Science, Data Engineering, or related field., At least 3 years of experience in machine learning engineering or applied AI development., Hands-on experience with ML frameworks like TensorFlow or PyTorch, from prototyping to deployment., Familiarity with cloud platforms such as AWS, Azure, or Databricks, and working with large datasets..

Key responsibilities:

Design, train, and refine machine learning models for real-world problems.

Build and maintain data ingestion and preprocessing pipelines.

Contribute to end-to-end ML workflows, including model deployment and monitoring.

Apply advanced AI techniques like transformers, LLMs, and reinforcement learning.

Job description

We’re looking for a Machine Learning Engineer to join our growing Data & AI team. In this role, you’ll help design, build, and deploy intelligent models and ML-powered workflows that solve real-world challenges at scale. You’ll work closely with data engineers, product owners, and AI specialists to turn ideas into production-ready solutions, embedding AI seamlessly into business processes.

What You’ll Do:

Model Development: Design, train, and refine machine learning models that tackle real business problems, ensuring they scale effectively in production environments.

Data Pipeline Engineering: Build and maintain robust data ingestion, preprocessing, and transformation pipelines for diverse data sources (structured and unstructured).

AI Workflow Integration: Contribute to end-to-end ML workflows—from serving and monitoring models to evaluating and iterating on their performance.

Advanced AI Techniques: Apply state-of-the-art approaches, including transformers, LLMs, RAG, embeddings, vector databases, predictive modeling, and reinforcement learning, to push the boundaries of what’s possible.

Model Monitoring & Optimization: Support ongoing evaluation and tuning of models to improve accuracy, efficiency, and reliability in production.

MLOps: Help establish best practices for CI/CD, testing, and automated deployment of AI models.

Agile Collaboration: Partner effectively with cross-functional teams in an agile setting, contributing to sprint planning, reviews, and collaborative problem-solving.

What You Bring:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related technical field.

3+ years of experience in machine learning engineering, applied AI development, or a similar role.

Strong, hands-on experience with ML frameworks such as TensorFlow or PyTorch, from prototyping to deployment.

Familiarity with cloud platforms (AWS, Azure, or Databricks) and experience delivering solutions at scale.

Solid understanding of working with large, complex datasets spanning structured and unstructured formats.

Sharp analytical and problem-solving skills with attention to data quality and model performance metrics.

Strong communication and collaboration abilities—you’re a team player who can explain technical concepts clearly and drive projects forward.

About Nimble Gravity

Nimble Gravity is a team of outdoor enthusiasts, adrenaline seekers, and experienced growth hackers. We love solving hard problems and believe the right data can transform and propel growth for any organization.

Nimble Gravity is an Equal Opportunity Employer and considers applicants for employment without regard to race, color, religion, sex, orientation, national origin, age, disability, genetics or any other basis forbidden under federal, state, or local law. Nimble Gravity considers all qualified applicants.

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