About Voidnix
Voidnix LLP builds and deploys AI and machine learning systems for organisations in financial services, technology, and enterprise software. We are a small engineering team, and this is a direct hire onto that team — you will be a Voidnix employee working on Voidnix engagements, not placed with or contracted out to a third party.
About the role
We are looking for an AI Engineer with around three years of experience to work hands-on across our engagements. You will own the technical decisions on your work: evaluating which models, tools, and frameworks fit each problem, validating the approach with a proof-of-concept, then building and deploying it. You will have direct exposure to the people using what you build.
What you'll do
- Build, train, and evaluate machine learning models for real business problems
- Choose the right approach for each problem — off-the-shelf LLM APIs, fine-tuning, or training a custom model
- Compare tools and frameworks on accuracy, cost, latency, and effort, and justify the choice
- Build proof-of-concepts to validate feasibility before full development
- Develop LLM-based features: RAG pipelines, document processing, chatbots, and API integrations
- Prepare and clean data, engineer features, and set up evaluation pipelines
- Deploy models as REST APIs and support them in production
- Translate requirements into technical scope and explain trade-offs in plain language
- Monitor deployed models, debug issues, and iterate based on real usage
- Track new models and tooling, and assess what is practically usable
- Document your work so it can be handed over and maintained
What we're looking for
- Around 3 years in AI/ML engineering, or software engineering with substantial ML work
- Strong Python, plus pandas, NumPy, and SQL
- Practical experience with scikit-learn and at least one deep learning framework (PyTorch or TensorFlow)
- Hands-on work with LLM APIs — prompt design, RAG, and vector databases
- Ability to build and deploy REST APIs (FastAPI or Flask)
- Comfortable with Git, Docker basics, and at least one cloud platform (AWS, GCP, or Azure)
- Judgment on when to use an existing model or API versus training something custom
- Able to read model documentation, benchmarks, and technical writeups and pull out what is usable
- Comfortable with ambiguous problems where the right approach is not decided upfront
- Clear written and spoken communication
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience
Nice to have
- MLOps exposure — MLflow, model versioning, monitoring
- LangChain, LlamaIndex, or LangGraph
- CI/CD pipelines
- Depth in NLP or computer vision
- Prior client-facing delivery experience
What we offer
- Remote work with a flexible schedule
- Variety — you will work across multiple domains and problem types rather than a single product
- Paid leave as per company policy
Interview process
- Application review
- A 30-minute introductory call
- A technical discussion covering your past ML work
- A short practical exercise or code walkthrough
- Final conversation with the founding team
We aim to complete the process within two to three weeks.
If you have GitHub projects, published work, or deployed AI applications, add the links to your resume — we weigh those heavily.
Pay: ₹700,000.00 - ₹800,000.00 per year
Benefits:
- Flexible schedule
- Work from home
Work Location: Remote
