13 days ago
Remote, IndiaMid Level / Senior
Responsibilities
- Develop, deploy, maintain, and scale robust AI and machine learning pipelines for internal and client projects.
- Deploy and optimize pre-trained and custom AI models, including LLMs and Generative AI technologies, in production environments.
- Convert model prototypes into scalable production-ready systems in collaboration with data scientists.
- Optimize model performance, latency, and cost efficiency across cloud platforms.
- Integrate AI/ML solutions with AWS, GCP, and Azure and use Docker and Kubernetes for consistent deployment.
- Apply MLOps practices including model versioning, monitoring, logging, maintenance, and CI/CD pipelines.
- Coordinate with software engineering teams, solution architects, data scientists, and other cross-functional partners.
Requirements
- Bachelor's or master's degree in Computer Science, Engineering, Artificial Intelligence, or a related quantitative field.
- 4 to 5 years of progressive experience in machine learning engineering, software development with an ML/AI focus, or a related role.
- 1 to 3 years of experience with ADK or other agentic frameworks.
- Strong Python programming skills and proficiency with TensorFlow, PyTorch, or Scikit-learn.
- Hands-on experience deploying pre-trained models such as LLMs or similar Generative AI technologies into production.
- Experience with AWS, GCP, Azure, Docker, and Kubernetes.
- Knowledge of data engineering principles, ETL/ELT processes, Git, machine learning pipeline orchestration, and scalable AI/ML systems.
- Familiarity with MLOps practices including model monitoring, logging, and CI/CD pipelines for AI assets.
- Strong communication and teamwork skills across cross-functional technical teams.
Benefits
- Fully remote work from home with no daily office travel requirement.
- Competitive total rewards package.
- Training allowance, professional development days, training opportunities, and certification support.
- Company-provided work-from-home equipment, including a laptop with a choice of operating system.
- Annual budget for personalizing the work environment.
- Annual wellness budget, paid vacation and sick days, and a paid day off for volunteering.
- Opportunities to blog during work hours and volunteer for a preferred charity.
Tech Stack
AWSAzureDockerGitGoogle CloudGoogle Cloud PlatformKubernetesPythonPyTorchscikit-learnSnowflakeTensorFlow
Categories
