Responsibilities
- Develop and deploy AI/ML models to solve business problems across various domains, including prediction, classification, and pattern detection
- Support use cases in NLP and Generative AI, including basic work with LLMs, prompt design, and text-based automation
- Build and maintain ML pipelines for data processing, model training, evaluation, and deployment
- Collaborate with Data Scientists, Data Engineers, and Software Engineers to integrate AI/ML features into production systems
- Share knowledge and guide team members on best practices in AI/ML implementation
- Explore and evaluate tools and frameworks that improve our AI/ML capabilities (e.g., Hugging Face, LangChain, OpenAI APIs)
- Assist in setting up basic ML-Ops workflows such as model versioning and monitoring
Requirements
- Bachelor's or Master’s degree in Computer Science, Data Science, or a related field
- 2-3 years in AI/ML engineering, with real-world project exposure
- Proficient in Python, with strong experience using frameworks like scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers
- Understanding of various ML techniques: supervised/unsupervised learning, time series, etc.
- Experience or strong interest in LLM, NLP, and prompt engineering.
- Comfortable working with either cloud-based platforms (e.g., GCP, Azure) or on-premise environments
- Experience working with cloud-based ML tools: GCP, Azure, or AWS
- Strong communication skills and ability to mentor or support adjacent roles
Responsibilities
- Develop and deploy AI/ML models to solve business problems across various domains, including prediction, classification, and pattern detection
- Support use cases in NLP and Generative AI, including basic work with LLMs, prompt design, and text-based automation
- Build and maintain ML pipelines for data processing, model training, evaluation, and deployment
- Collaborate with Data Scientists, Data Engineers, and Software Engineers to integrate AI/ML features into production systems
- Share knowledge and guide team members on best practices in AI/ML implementation
- Explore and evaluate tools and frameworks that improve our AI/ML capabilities (e.g., Hugging Face, LangChain, OpenAI APIs)
- Assist in setting up basic ML-Ops workflows such as model versioning and monitoring
Requirements
- Bachelor's or Master’s degree in Computer Science, Data Science, or a related field
- 2-3 years in AI/ML engineering, with real-world project exposure
- Proficient in Python, with strong experience using frameworks like scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers
- Understanding of various ML techniques: supervised/unsupervised learning, time series, etc.
- Experience or strong interest in LLM, NLP, and prompt engineering.
- Comfortable working with either cloud-based platforms (e.g., GCP, Azure) or on-premise environments
- Experience working with cloud-based ML tools: GCP, Azure, or AWS
- Strong communication skills and ability to mentor or support adjacent roles