hybrid
Machine Learning Engineer
Machine Learning Engineer
The Machine Learning Engineer will be responsible for designing, developing, and deploying NLP, CV, and recommendation systems, as well as building and maintaining end-to-end ML pipelines. This role requires strong coding skills in Python, experience with deep learning frameworks like TensorFlow/PyTorch, and familiarity with cloud platforms like AWS/GCP.
About the role
About the Role
ClanX is looking for a Machine Learning Engineer to join their team in Bengaluru. This role involves designing, developing, and deploying cutting-edge AI solutions, with a strong focus on NLP, CV, and recommendation systems.
Responsibilities
- Design, develop, and deploy NLP, CV, and recommendation systems.
- Train and implement deep learning models.
- Research and explore novel ML architectures.
- Build and maintain end-to-end ML pipelines.
- Collaborate across product, design, and engineering teams.
- Work closely with business stakeholders to shape product features.
- Ensure high scalability and performance of AI solutions.
- Uphold best practices in engineering and contribute to a culture of excellence.
- Actively participate in R&D and innovation within the team.
Requirements
- 2+ years of relevant experience in ML and AI roles.
- Strong grasp of ML, deep learning, and model deployment.
- Proficient in Python and libraries like numpy, pandas, sklearn, etc.
- Experience with TensorFlow/Keras or PyTorch.
- Familiar with AWS/GCP platforms.
- Strong coding skills and ability to ship production-ready solutions.
- Bachelor's/Master's in Engineering or related field.
- Curious, self-driven, and a fast learner.
- Passionate about NLP, LLMs, and state-of-the-art AI technologies.
- Comfortable with collaboration across globally distributed teams.
Preferred (Not Mandatory):
- Experience with Django, databases, and full-stack environments.
- Familiarity with OCR and PDF processing.
- Competitive programming or Kaggle participation.
- Prior work with distributed teams across time zones.