ML Engineer
Description For ML Engineer
Join a well-funded data distribution strategy company that has recently secured $5M in funding to revolutionize AI-driven data infrastructure. As a Machine Learning Engineer, you'll be responsible for designing, training, and deploying high-performance ML models that drive intelligent automation, predictive analytics, and data optimization. The role involves working with cutting-edge technologies including TensorFlow, PyTorch, and cloud-based ML platforms, while handling large-scale datasets using modern big data frameworks.
You'll be part of a global team developing solutions for seamless, secure, and scalable data exchange. The position offers the opportunity to work with elite engineers worldwide in a fully remote environment. The company maintains a high-performance culture focused on results-driven innovation, without bureaucratic overhead.
The ideal candidate brings 3+ years of ML/AI experience, strong Python skills, and expertise in cloud platforms and MLOps. You'll work on implementing end-to-end data processing workflows, optimizing data processing efficiency, and integrating ML models into production systems using modern containerization and orchestration tools.
This role offers competitive compensation in the top market range, along with the excitement of joining a well-funded startup at the forefront of AI and data strategy. You'll have the chance to influence the future of data distribution while working with a team that values innovation and technical excellence.
Responsibilities For ML Engineer
- Design and optimize machine learning models for data distribution, anomaly detection, and predictive analytics
- Implement end-to-end data processing workflows for real-time and batch inference
- Work with large-scale datasets using Spark, Dask, or Ray
- Deploy ML models into production using APIs, microservices, and containerized environments
- Experiment with ML advancements and improve model performance
Requirements For ML Engineer
- 3+ years of experience in machine learning, deep learning, or AI model development
- Strong Python skills with proficiency in TensorFlow, PyTorch, Scikit-learn, and NumPy
- Experience with big data frameworks (Spark, Dask, Kafka, or Ray)
- Cloud expertise with AWS SageMaker, GCP Vertex AI, or Azure ML
- Familiarity with SQL, NoSQL, and distributed data storage
- Experience with Docker, Kubernetes, and CI/CD pipelines
- Strong problem-solving and research skills
Benefits For ML Engineer
- Well-funded startup with $5M in funding
- Opportunity to build cutting-edge AI-driven data infrastructure
- Competitive salaries in the top 5% to 1% market range
- Fully remote work environment
- Global team collaboration
- High-performance culture with no micromanagement
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