Machine Learning Engineer

Remote -

United States

J-00001

About Coastaloupe

Coastaloupe is at the forefront of AI-driven innovation, building cutting-edge machine learning solutions that transform industries. Focused on solving real-world challenges using state-of-the-art models and scalable AI systems. A great fit for those looking to work on impactful projects in a collaborative and fast-paced environment.

What You’ll Do

  • Design, develop, and deploy machine learning models for real-world applications.
  • Optimize models for efficiency, scalability, and deployment in cloud and/or edge environments.
  • Work with deep learning architectures such as CNNs, RNNs, Transformers, and SSMs.
  • Fine-tune pre-trained LLMs and integrate them into production workflows.
  • Collaborate with data engineers to process and prepare large-scale datasets.
  • Conduct model performance evaluation and optimization (Quantization, Pruning, Distillation, etc.).
  • Apply MLOps best practices for model deployment, monitoring, and retraining.

Preferred Experience

  • 3+ years of experience in machine learning and deep learning model development.
  • Strong proficiency in Python and ML frameworks like TensorFlow, PyTorch.
  • Hands-on experience with LLMs, RAG, and Transformer-based architectures.
  • Experience deploying models using AWS, GCP, or Azure.
  • Familiarity with model optimization techniques for edge and cloud AI.
  • Knowledge of MLOps tools (Docker, Kubernetes, MLflow, etc.).
  • Strong problem-solving skills and ability to work in an agile development environment.

Bonus Points For

  • Experience in Edge AI, Neuromorphic Computing, or Hardware-aware ML.
  • Contributions to open-source ML projects or research publications.
  • Experience with Graph Neural Networks (GNNs) or SSMs.

Why Join Coastaloupe?

✅ Work on cutting-edge AI/ML projects that drive real-world impact.

✅ Competitive salary and benefits.

✅ Flexible work arrangements (remote/hybrid options).

✅ Opportunities for career growth, research, and innovation.

This isn’t just about filling a role—it’s about contributing to a culture rooted in innovation, curiosity, and meaningful impact. If that resonates, apply, follow the page, and connect! 🚀

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Machine Learning Engineer.

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