Description

Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Minimum of two years of professional experience in developing AI/ML solutions, with a strong track record of successful project delivery.
Proficiency in programming languages such as Python / C++ / R / Scala, with experience in building machine learning and deep learning models libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, Spark MLlib, OpenCV, scipy, nltk, transformers, langchain, etc.
Strong foundation of deep learning, computer vision, natural language processing, and generative AI concepts.
Solid understanding of machine learning concepts and techniques, including supervised, unsupervised, and reinforcement learning algorithms.
Experience with LLMs, training them on custom data, as well as third-party LLM API (like OpenAI API) integrations.

Requirements

Key Responsibilities Design, build, and deploy machine learning models (supervised, unsupervised, deep learning) Develop and optimize data pipelines for model training and inference Implement and maintain production-ready ML systems (MLOps) Work with large datasets: data cleaning, feature engineering, transformation Evaluate model performance and continuously improve accuracy and efficiency Collaborate with cross-functional teams to integrate ML solutions into products Stay updated with the latest advancements in AI/ML and apply them when relevant

Required Skills & Qualification

Strong programming skills in Python (preferred), or Java/Scala

Experience with ML frameworks

TensorFlow PyTorch scikit-learn Solid understanding of algorithms: regression, classification, clustering, NLP, deep learning Knowledge of statistics and probability Experience with data handling tools: Pandas, NumPy, SQL

Familiarity with cloud platforms

AWS, Google Cloud Platform, Microsoft Azure Understanding of MLOps tools (Docker, Kubernetes, CI/CD pipelines)

Preferred Qualifications

Experience with NLP, Computer Vision, or Generative AI Knowledge of big data tools (Spark, Hadoop)
Experience with APIs and microservices architecture Familiarity with model monitoring and deployment frameworks

Key Skills

Education

Any Graduate