
We are looking for a skilled ML Engineer with 3–5 years of experience in building and deploying production-grade AI solutions, particularly around LLMs, RAG systems, and agentic AI frameworks. The role involves designing end-to-end ML architectures, optimizing models at scale, and delivering client-ready AI solutions. You will collaborate closely with stakeholders, mentor junior engineers, and drive AI projects from experimentation to production.
What will you need to be successful in this role?
Core Technical Skills
• Strong hands-on experience with Python for ML/AI (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow)
• Proven experience deploying production LLM applications with 1M+ tokens processed
• Advanced prompt engineering expertise including ReAct, meta-prompting, and function calling
• Production experience with RAG systems including hybrid search and re-ranking
• Deep understanding of embedding models and vector databases at scale
• Experience with agentic AI frameworks (LangGraph, CrewAI, or AutoGen)
• Strong knowledge of LLM evaluation frameworks (RAGAS, LLM-as-judge patterns)
• Experience implementing multi-agent systems and orchestration
• Proficiency with cloud ML platforms (AWS SageMaker, Azure ML, or Vertex AI)
Advanced Capabilities
• Experience with model fine-tuning (LoRA, QLoRA, PEFT, instruction tuning)
• Knowledge of knowledge graphs and graph-based RAG implementations
• Understanding of model hosting, inference optimization, and cost management
• Experience with MLOps pipelines, CI/CD for ML, and model versioning
• Ability to architect end-to-end ML solutions from data ingestion to deployment
• Experience with data pipelines and ETL for ML workflows
• Proficiency in containerization and orchestration (Docker, Kubernetes)
Client Engagement & Delivery
• Experience presenting technical solutions to clients and stakeholders
• Ability to translate business requirements into technical ML solutions
• Track record of delivering client POCs and production implementations
• Experience creating technical documentation and implementation guides
Good to have
• Experience hosting private LLMs (7B-13B models on-premises or cloud)
• Knowledge of graph databases (Neo4j) and graph neural networks
• Experience with streaming and real-time ML inference
• Published research papers or contributions to open-source ML projects
• DeepLearning.AI certifications in Agentic AI, RAG, or Finetuning
• AWS/Azure ML certifications or working towards them
Competencies
• Excellent verbal and written communication skills
• Strong mentoring ability for junior ML engineers
• Self-driven with ability to work independently on complex problems
• Excellent problem-solving skills with systematic debugging approach
• Proactive ownership of projects from ideation to deployment
• Ability to stay current with rapidly evolving AI/ML landscape
• Excellent academic record – B.E./B.Tech, MCA,

About Byteridge
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Kognitos is a cutting-edge automation platform that combines the power of Generative AI and Natural
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technologies.
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microservices and cloud-based architectures.
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optimization.
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software development methodologies, such as Agile, DevOps, and CI/CD.
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ensure smooth operations.
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practices.
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improvements to the technology stack to increase efficiency and scalability.
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meets customer needs.
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- B.S. or higher degree in Computer Science/Engineering or similar field or equivalent work experience
- 4-20 years of industry experience (or equivalent)
- Proficient in Python programming language
- Experience with modern software development practices and methodologies, including Agile, DevOps,
and Continuous Integration/Continuous Delivery (CI/CD).
- Experience with large-scale distributed systems, microservices, and cloud-based architectures.
- Strong understanding of software design patterns, algorithms, data structures, and database technologies.
- A natural problem solver, with the ability to identify problems and lead the development of a solution.
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Details
- Work from home
What you will be working on?
You'll be a part of the core team and will be working with the founders in building and iterating upon the core product.
How you can grow with us?
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Will be working on the bleeding edge technologies of IoT which are not usually accessible to software engineers.
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Will get exposure to IoT Hardware and Industrial Infrastructure.
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Will get to deliver on-time, quality software in the challenging domains of Energy/IoT/Automation.
We appreciate the following traits!
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Will be dealing with the web app, mobile app, frontend, backend, etc. So, you need to be flexible in getting the work done.
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Need not be proficient in all of these but you can trump any of this by being a quick learner and a hard worker.
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Should be familiar with the transition from the development phase to the deployment phase.











