Inferigence Quotient
https://inferq.comAbout
Deep Tech Startup Focusing on Autonomy and Intelligence for Unmanned Systems. Guidance and Navigation, AI-ML, Computer Vision, Information Fusion, LLMs, Generative AI, Remote Sensing
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Jobs at Inferigence Quotient
The selected candidate is required to fine tune LLM models, train them in distributed mode using SLURM framework, perform the necessary data engineering, training process monitoring and tuning, analysis, and documentation.
Python
NodeJS (Node.js)
Docker
Javascript3-5 years of experience as full stack developer with essential requirements on the following technologies: FastAPI, JavaScript, React.js-Redux, Node.js, Next.js, MongoDB, Python, Microservices, Docker, and MLOps.
Experience in Cloud Architecture using Kubernetes (K8s), Google Kubernetes Engine, Authentication and Authorisation Tools, DevOps Tools and Scalable and Secure Cloud Hosting is a significant plus.
Ability to manage a hosting environment, ability to scale applications to handle the load changes, knowledge of accessibility and security compliance.
Testing of API endpoints.
Ability to code and create functional web applications and optimising them for increasing response time and efficiency. Skilled in performance tuning, query plan/ explain plan analysis, indexing, table partitioning.
Expert knowledge of Python and corresponding frameworks with their best practices, expert knowledge of relational databases, NoSQL.
Ability to create acceptance criteria, write test cases and scripts, and perform integrated QA techniques.
Must be conversant with Agile software development methodology. Must be able to write technical documents, coordinate with test teams. Proficiency using Git version control.
Python
Deep Learning
Machine Learning (ML)
C++AI based systems design and development, entire pipeline from image/ video ingest, metadata ingest, processing, encoding, transmitting.
Implementation and testing of advanced computer vision algorithms.
Dataset search, preparation, annotation, training, testing, fine tuning of vision CNN models. Multimodal AI, LLMs, hardware deployment, explainability.
Detailed analysis of results. Documentation, version control, client support, upgrades.
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