Machine Learning Engineer

Role Description

Location: Trivandrum / Kochi

Experience: 6 to 8 years

Who We Are

Join our ML R&D team where we work on both fascinating and challenging problems, applying cutting-edge Machine Learning techniques to solve complex issues like Document Understanding (AI). We have a production-ready solution that competes with industry leaders in multiple aspects. We challenge the status quo, reason from first principles, and continuously push the boundaries of ML. Our team works on solving problems with limited or no training data and strives for excellence in both innovative research and practical solutions.

As a member of the team, you will work on feature engineering, representation learning, and transfer learning to build models from scratch, adapt them for real-world problems, and deploy them at scale in production environments.

Key Responsibilities

• Applied ML Experience:
• Strong problem framing skills: deciding when to use supervised, self-supervised, or reinforcement learning (RL).
• Expertise in data wrangling, including techniques like Weak/Distant Supervision and Pseudo-labelling.
• Strong experience in Exploratory Data Analysis (EDA), data preparation, labelling, and augmentation.
• Deep understanding of end-to-end modelling (ML, DL, RL) and ability to choose between single models, ensembles, or mixture of experts.
• Good grasp of mathematical concepts such as Mathematical Induction, Tree Induction, Deep Learning, and optimization algorithms (e.g., SGD).
• Transfer Learning:
• Experience with N-shot learning or its variants, and proficient in fine-tuning models.
• ML/DL Specializations:
• Proven industry or research experience in domains such as Time Series Modelling, Computer Vision, Natural Language Processing (NLP), and Reinforcement Learning (RL).
• Model Deployment:
• Experience deploying machine learning models into production using tools like TFServe, Seldon, or custom model serving.
• Ability to optimize solutions for performance and scalability.
• Collaboration and Mentorship:
• Collaborate with cross-functional teams, including engineers, researchers, and product stakeholders, to create cutting-edge AI solutions.
• Mentor junior researchers and help drive the overall research agenda.
  

Must-Have Skills

• 6+ years of industry experience or 1-2 years of academic experience in applied Machine Learning.
• Strong expertise in problem framing, including selecting appropriate ML paradigms like supervised, unsupervised, or RL.
• Proficient in data wrangling, EDA, data preparation, and data augmentation.
• Strong experience in end-to-end model development for ML, DL, RL, and use of algorithms like SGD.
• Deep knowledge of TensorFlow or PyTorch for ML/DL model development.
• Experience with transfer learning and fine-tuning.
• Familiarity with Kaggle and GitHub portfolios showcasing original ML repositories and projects.
• Proven ability to implement and deploy ML models into production environments.
• Solid understanding of model optimization for scalability and performance.
• Strong communication skills for collaborating with stakeholders and mentoring junior team members.
  
  

Good-to-Have Skills

• Publications: Original 1st author papers in reputed ML journals or conferences.
• Patents: AI or Automation-specific patents are a plus.
• MLOps: Experience with Kubeflow, Mlflow, Airflow, or SparkML for running machine learning experiments.
• Familiarity with cloud-based platforms (AWS, GCP, Azure) for AI/ML.
• Data Engineering skills to ensure smooth data flows between systems and databases.
• Experience implementing custom ML code (e.g., implementing algorithms like SGD) when needed.
• Experience with containerization (Docker) and Kubernetes for deploying and managing models at scale.
• Background in Computer Science or IT, with a good understanding of statistics and probability.
  
  

Skills

Machine Learning,Artificial Intelligence,Python