Developer III – AI/ML Engineer Full-time

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.<