Ml Engineer

Summary

Join a well-funded, fast-growing data distribution strategy company that recently secured $5M in funding. They are building a global team and seeking a Machine Learning Engineer to design, train, and deploy high-performance ML models. This role involves developing and deploying ML models, building scalable ML pipelines, optimizing data processing, integrating ML into production systems, and experimenting with new approaches. The company offers top-tier compensation, a fully remote and global team, and a high-performance culture. This is an opportunity to be part of a cutting-edge AI startup shaping the future of data distribution strategy.

Requirements

• 3+ years of experience in machine learning, deep learning, or AI model development
• Strong Python skills – Proficiency in TensorFlow, PyTorch, Scikit-learn, and NumPy
• Experience with big data frameworks (Spark, Dask, Kafka, or Ray)
• Cloud expertise – Hands-on experience with AWS SageMaker, GCP Vertex AI, or Azure ML
• Database & Data Processing – Familiarity with SQL, NoSQL, and distributed data storage (Snowflake, BigQuery, MongoDB, or Redis)
• MLOps & Deployment – Experience with Docker, Kubernetes, and CI/CD pipelines for ML model deployment
• Strong problem-solving and research skills – Ability to optimize ML models for real-world applications

Responsibilities

• Develop & Deploy ML Models – Design and optimize machine learning models for data distribution, anomaly detection, and predictive analytics
• Build Scalable ML Pipelines – Implement end-to-end data processing workflows for real-time and batch inference using Python, TensorFlow, PyTorch, and cloud-based ML platforms
• Optimize Data Processing – Work with large-scale datasets using Spark, Dask, or Ray to enhance data ingestion, transformation, and storage efficiency
• Integrate ML into Production Systems – Deploy ML models into production using APIs, microservices, and containerized environments (Docker, Kubernetes)
• Experiment & Innovate – Stay ahead of ML advancements, test new approaches, and improve model performance for accuracy, efficiency, and scalability

Benefits

• $5M in funding – Be part of a well-funded, high-growth AI startup
• Cutting-Edge ML Work – Build AI-driven data infrastructure shaping the future of data distribution strategy
• Top-Tier Compensation – Competitive salaries in the top 5% to 1% market range
• Fully Remote & Global Team – Work with elite engineers from around the world
• High-Performance Culture – No micromanagement, no bureaucracy—just results-driven innovation