Indore, Madhya Pradesh, India
Information Technology
Full-Time
Sutherland
Overview
Company Description
Sutherland is at the forefront of AI-driven innovation, specializing in Generative AI (GenAI) and Large Language Models (LLMs). We build intelligent applications that transform industries by leveraging cutting-edge AI technologies. Join us to create tools that redefine developer productivity.
Job Description
Role Overview
We are seeking a Software Engineer with MLOps skills to contribute to the deployment, automation, and monitoring of GenAI and LLM-based applications. You will work closely with AI researchers, data engineers, and DevOps teams to ensure seamless integration, scalability, and reliability of AI systems in production.
Key Responsibilities
Technical Skills
Sutherland is at the forefront of AI-driven innovation, specializing in Generative AI (GenAI) and Large Language Models (LLMs). We build intelligent applications that transform industries by leveraging cutting-edge AI technologies. Join us to create tools that redefine developer productivity.
Job Description
Role Overview
We are seeking a Software Engineer with MLOps skills to contribute to the deployment, automation, and monitoring of GenAI and LLM-based applications. You will work closely with AI researchers, data engineers, and DevOps teams to ensure seamless integration, scalability, and reliability of AI systems in production.
Key Responsibilities
- Deployment & Integration
- Assist in deploying and optimizing GenAI/LLM models on cloud platforms (AWS SageMaker, Azure ML, GCP Vertex AI).
- Integrate AI models with APIs, microservices, and enterprise applications for real-time use cases.
- MLOps Pipeline Development
- Contribute to building CI/CD pipelines for automated model training, evaluation, and deployment using tools like MLflow, Kubeflow, or TFX.
- Implement model versioning, A/B testing, and rollback strategies.
- Automation & Monitoring
- Help automate model retraining, drift detection, and pipeline orchestration (Airflow, Prefect).
- Assist in designing monitoring dashboards for model performance, data quality, and system health (Prometheus, Grafana).
- Data Engineering Collaboration
- Work with data engineers to preprocess and transform unstructured data (text, images) for LLM training/fine-tuning.
- Support the maintenance of efficient data storage and retrieval systems (vector databases like Pinecone, Milvus).
- Security & Compliance
- Follow security best practices for MLOps workflows (model encryption, access controls).
- Ensure compliance with data privacy regulations (GDPR, CCPA) and ethical AI standards.
- Collaboration & Best Practices
- Collaborate with cross-functional teams (AI researchers, DevOps, product) to align technical roadmaps.
- Document MLOps processes and contribute to reusable templates.
Technical Skills
- Languages: Proficiency in Python and familiarity with SQL/Bash.
- ML Frameworks: Basic knowledge of PyTorch/TensorFlow, Hugging Face Transformers, or LangChain.
- Cloud Platforms: Experience with AWS, Azure, or GCP (e.g., SageMaker, Vertex AI).
- MLOps Tools: Exposure to Docker, Kubernetes, MLflow, or Airflow.
- Monitoring: Familiarity with logging/monitoring tools (Prometheus, Grafana).
- 2+ years of software engineering experience with exposure to MLOps/DevOps.
- Hands-on experience deploying or maintaining AI/ML models in production.
- Understanding of CI/CD pipelines and infrastructure as code (IaC) principles.
- Bachelor’s degree in Computer Science, Data Science, or related field.
- Familiarity with LLM deployment (e.g., GPT, Claude, Llama) or RAG systems.
- Knowledge of model optimization techniques (quantization, LoRA).
- Certifications in cloud platforms (AWS/Azure/GCP) or Kubernetes.
- Contributions to open-source MLOps projects.
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