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ai-mlRemote (Nepal)full-time
🤖 Senior MLOps/Data Engineer (Computer Vision & AWS Focus)
OVERVIEW
We are seeking a skilled Senior MLOps/Data Engineer with 5-6 years of experience to design, build, and maintain scalable ML pipelines and data infrastructure for innovative Israeli deep tech startups. Priority will be given to candidates with expertise in computer vision-related pipelines (e.g., image processing, model deployment for CV tasks). The ideal candidate will have a proven track record of automating ML workflows, managing data pipelines on AWS, ensuring model reproducibility, and optimizing for production-scale AI systems. Excellent communication skills, the ability to translate business objectives into technical tasks, and a strong aptitude for remote work are essential.
RESPONSIBILITIES
- 01Design, implement, and maintain end-to-end ML pipelines, with a focus on computer vision workflows (e.g., data ingestion for images/videos, feature extraction, model training/deployments).
- 02Build and optimize data infrastructure using AWS services to support large-scale data processing, storage, and ML operations.
- 03Automate CI/CD for ML models, including versioning, monitoring, and retraining processes.
- 04Collaborate with data scientists, AI engineers, and cross-functional teams to deploy models into production and align with business objectives.
- 05Translate complex business requirements into actionable data and ML engineering tasks.
- 06Ensure data quality, security, and compliance in pipelines, with emphasis on handling high-volume CV datasets.
- 07Monitor and troubleshoot ML systems for performance, drift, and scalability issues.
- 08Implement Infrastructure as Code (IaC) and orchestration for ML workflows on AWS.
- 09Write clean, maintainable code and documentation, and participate in code reviews.
- 010Communicate effectively with remote teams to ensure alignment on project goals.
- 011Mentor junior engineers and contribute to team knowledge sharing on MLOps best practices.
REQUIREMENTS
- Education: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
- Experience: 5-6 years of professional experience in MLOps, Data Engineering, or related roles, with hands-on work in building ML pipelines; priority for computer vision expertise (e.g., OpenCV, TensorFlow/PyTorch for CV).
- Deep expertise in AWS services for data and ML (e.g., S3, EMR, SageMaker, Glue, Lambda, ECS/EKS).
- Strong proficiency in tools like Airflow, Kubeflow, or MLflow for pipeline orchestration.
- Proficiency in programming languages such as Python, and big data technologies (e.g., Spark, Hadoop).
- Proven ability to break down business objectives into technical tasks, excellent English communication, and self-motivation for remote work.
- Familiarity with containerization (Docker), orchestration (Kubernetes), and Git.
- Bonus: Experience with computer vision-specific tools (e.g., labeling pipelines, augmentation), AWS certifications, or integrating LLMs/ML models in production.