Posted:2 months ago|
Platform:
Work from Office
Full Time
Collect business requirements and translate them into machine learning solutions. Prepare data for ML applications. Build ML models using supervised, unsupervised, or deep learning techniques. Optimize AI solutions for latency, speed, and accuracy, ensuring they are performant under high demand. Develop and integrate models into existing systems, ensuring smooth operation in the production environment. Stay up-to-date with the latest AI/ML trends and apply new techniques to improve existing systems. Collaborate with other team members. Requirements and Skills Should be interested to work in a startup culture/ecosystem. Willingness to learn with a "Never Die Attitude." Ability to work independently as well as in a team. Skilled in LLaMA models and transformer-based architectures, with experience in fine-tuning and adapting LLMs for specific tasks. Strong understanding of LLMs, RAG, and vector databases. Skilled in Python and ML libraries like TensorFlow, PyTorch, scikit-learn, and experience with data manipulation libraries (e.g., Pandas, NumPy). Knowledge of deploying ML models in production environments and familiarity with MLOps tools like Docker, Kubernetes, and CI/CD platforms. Proficiency in generative AI methodologies such as text generation, style transfer, speech recognition, image synthesis, and familiarity with tools and diffusion models. Strong commitment to ethical AI practices, including transparency, fairness, bias mitigation, and compliance with data privacy laws. Expertise in scaling machine learning models for high-traffic environments.
NSE Cogencis
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