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AI ML Engineer
2 months ago
Note: We are preferring candidates from Top Engineering institutes and Product firm Exp.
About Position
As a crucial member of our team, you'll play a pivotal role across the entire machine learning lifecycle,contributing to our conversational AI bots, RAG system and traditional ML problem solving for ourobservability platform. Your tasks will encompass both operational and engineering aspects, includingbuilding production-ready inference pipelines, deploying and versioning models, and implementingcontinuous validation processes. On the LLM side you'll fine-tune generative AI models, design agentic language chains, and prototype recommender system experiments.
Role: AL ML Engineer
Location: Bengaluru / hyderabad
Experience : 2-7 years
What You'll Do
• Fine-tuning generative AI models to enhance performance.
• Designing AI Agents for conversational AI applications.
• Experimenting with new techniques to develop models for observability use cases
• Building and maintaining inference pipelines for efficient model deployment.
• Managing deployment and model versioning pipelines for seamless updates.
• Developing tooling to continuously validate models in production environments.
What we're looking for:
• 2-6 Years Demonstrated proficiency in software engineering design practices.
• Bachelor's or advanced degree in Computer Science, Engineering, Mathematics, or a related
field. Advanced degree (Master's or Ph.D.) preferred.
• Experience working with transformer models and text embeddings.
• Proven track record of deploying and managing ML models in production environments.
• Familiarity with common ML/NLP libraries such as PyTorch, Tensorflow, HuggingFace
Transformers, and SpaCy.
• Preferred experience developing production-grade applications in Python.
• Proficiency in Kubernetes and containers.
• Familiarity with concepts/libraries such as sklearn, kubeflow, argo, and seldon.
• Expertise in Python, C++, Kotlin, or similar programming languages.
• Experience designing, developing, and testing scalable distributed systems.
• Familiarity with message broker systems (e.g., Kafka, RabbitMQ).
• Knowledge of application instrumentation and monitoring practices.
• Experience with ML workflow management, like AirFlow, Sagemaker, etc.
• Familiarity with the AWS ecosystem.
• Past projects involving the construction of agentic language chains.
Benefits
• Competitive salary and benefits package
• Culture focused on talent development with quarterly promotion cycles and companysponsored higher education and certifications
• Opportunity to work with cutting-edge technologies
• Employee engagement initiatives such as project parties, flexible work hours, and Long Service
awards,Annual health check-ups, Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents
