YASH Technologies - AI Operations Engineer

We are looking forward to hire AI/ML Professionals in the following areas

Job Description :

AI Ops Engineer

Experience required : 3 - 4 years

Key Responsibilities

AI Model Deployment & Integration :

- Deploy and manage AI/ML models, including traditional machine learning and GenAI solutions (e.g., LLMs, RAG systems).

- Implement automated CI/CD pipelines for seamless deployment and scaling of AI models.

- Ensure efficient model integration into existing enterprise applications and workflows in collaboration with AI Engineers.

- Optimize AI infrastructure for performance and cost efficiency in cloud environments (AWS, Azure, GCP).

Monitoring & Performance Management :

- Develop and implement monitoring solutions to track model performance, latency, drift, and cost metrics.

- Set up alerts and automated workflows to manage performance degradation and retraining triggers.

- Ensure responsible AI by monitoring for issues such as bias, hallucinations, and security vulnerabilities in GenAI outputs.

- Collaborate with Data Scientists to establish feedback loops for continuous model improvement.

Automation & MLOps Best Practices :

- Establish scalable MLOps practices to support the continuous deployment and maintenance of AI models.

- Automate model retraining, versioning, and rollback strategies to ensure reliability and compliance.

- Utilize infrastructure-as-code (Terraform, CloudFormation) to manage AI pipelines.

Security & Compliance :

- Implement security measures to prevent prompt injections, data leakage, and unauthorized model access.

- Work closely with compliance teams to ensure AI solutions adhere to privacy and regulatory standards (HIPAA, GDPR).

- Regularly audit AI pipelines for ethical AI practices and data governance.

Collaboration & Process Improvement :

- Work closely with AI Engineers, Product Managers, and IT teams to align AI operational processes with business needs.

- Contribute to the development of AI Ops documentation, playbooks, and best practices.

- Continuously evaluate emerging GenAI operational tools and processes to drive innovation.

Qualifications & Skills :

Education :

- Bachelors or Masters degree in Computer Science, Data Engineering, AI, or a related field.

- Relevant certifications in cloud platforms (AWS, Azure, GCP) or MLOps frameworks are a plus.

Experience :

- 3+ years of experience in AI/ML operations, MLOps, or DevOps for AI-driven solutions.

- Hands-on experience deploying and managing AI models, including LLMs and GenAI solutions, in production environments.

- Experience working with cloud AI platforms such as Azure AI, AWS SageMaker, or Google Vertex AI.

Technical Skills :

- Proficiency in MLOps tools and frameworks such as MLflow, Kubeflow, or Airflow.

- Hands-on experience with monitoring tools (Prometheus, Grafana, ELK Stack) for AI performance tracking.

- Experience with containerization and orchestration tools (Docker, Kubernetes) to support AI workloads.

- Familiarity with automation scripting using Python, Bash, or PowerShell.

- Understanding of GenAI-specific operational challenges such as response monitoring, token management, and prompt optimization.

- Knowledge of CI/CD pipelines (Jenkins, GitHub Actions) for AI model deployment.

- Strong understanding of AI security principles, including data privacy and governance considerations.

Soft Skills :

- Strong problem-solving skills with the ability to troubleshoot complex AI operational issues.

- Excellent communication skills to effectively collaborate with cross-functional stakeholders.

- Proactive and results-driven mindset with a focus on operational efficiency and scalability.

- Ability to work effectively in a fast-paced, dynamic environment.

At YASH, you are empowered to create a career that will take you to where you want to go while working in an inclusive team environment. We leverage career-oriented skilling models and optimize our collective intelligence aided with technology for continuous learning, unlearning, and relearning at a rapid pace and scale.

Our Hyperlearning workplace is grounded upon four principles. Flexible work arrangements, Free spirit, and emotional positivity. Agile self-determination, trust, transparency, and open collaboration. All Support needed for the realization of business goals,. Stable employment with a great atmosphere and ethical corporate culture. Apply now .