Job
Description
Role Description Location: Trivandrum / Kochi Experience: 3 to 5 years We are looking for flexible and talented individuals with a solid background in Machine Learning. You should ideally have 3-5 years of industry experience or 1-2 years of academic experience. You should be able to thrive in a collaborative environment and handle complex ML problems across different domains. Key Responsibilities Apply cutting-edge ML techniques to solve complex business problems.Problem framing: Deciding the right approach, whether it's Supervised, Self-Supervised, or Reinforcement Learning (RL).Data wrangling: Using techniques like Weak/Distant Supervision, Pseudo-labelling, and robust EDA (Exploratory Data Analysis).Model development: End-to-end modeling experience in ML, DL, and RL.Transfer Learning: Expertise in N-shot learning and fine-tuning pre-trained models.Work across various ML/DL verticals, including Time Series Modelling, Vision, NLP, and RL.Deploy ML/DL models into production, optimizing for performance and scalability.Collaborate with teams to deliver automated solutions and run experiments using MLOps tools like Kubeflow, Mlflow, Airflow, or SparkML.Maintain a GitHub portfolio with original ML repositories and contribute to the Kaggle community.Publish original first-author papers in reputed ML journals or conferences, or file patents related to AI or Automation. Must-Have Skills Programming: Expertise in Python or R.Applied ML Experience: Proven experience in problem framing, including when to use Supervised vs Self-Supervised or Reinforcement Learning (RL).Data Wrangling: Experience with techniques like Weak/Distant Supervision, Pseudo-labelling, EDA, and data augmentation.End-to-End Modeling: Solid experience in Machine Learning, Deep Learning, and Reinforcement Learning (RL).Transfer Learning: Strong experience with N-shot learning and fine-tuning pre-trained models.ML/DL Libraries: Proficiency in TensorFlow or PyTorch.MLOps: Hands-on experience with Kubeflow, Mlflow, Airflow, or SparkML for running and managing experiments.Model Deployment: Experience deploying ML models using tools such as TFServe, Seldon, or custom model serving techniques.GitHub/Kaggle Portfolio: Active GitHub repository with original contributions and a decent Kaggle leaderboard position.Problem-Solving: Strong problem-solving and mathematical skills, including optimization algorithms like SGD.Research: Experience in publishing 1st author papers in reputed ML conferences or journals. Good-to-Have Skills Computer Science/IT Background: A background in Computer Science or Information Technology.Statistics & Probability: Exposure to statistics and probability concepts.Docker & Kubernetes: Experience running dockerized code, as we are a Kubernetes-centric shop.Patents: AI or Automation-specific patents.Additional ML/DL Domains: Research or industry experience in other domains such as Vision, Time Series, or NLP. Education Bachelor's Degree in Computer Science, Engineering, or a related field. Skills Artificial Intelligence,Machine Learning,Deep Learning
