AI Engineer at Weekday AI

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

25 Dec, 25

Salary

0.0

Posted On

26 Sep, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, TensorFlow, PyTorch, Scikit-learn, Keras, OpenCV, NLTK, Hugging Face Transformers, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Cloud Platforms, MLOps, Data Preprocessing, Problem Solving

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min Experience: 4 years Location: Gurgaon, NCR JobType: full-time We are seeking a highly skilled and innovative AI Engineer with 4–8 years of hands-on experience in artificial intelligence, machine learning, and deep learning. This role requires a professional who can design, build, and deploy AI-driven solutions that solve real-world problems, optimize business processes, and create value across products and services. The ideal candidate will have strong expertise in AI frameworks, algorithms, and tools, along with the ability to work collaboratively in a dynamic, fast-paced environment. Key Responsibilities Design, develop, and deploy scalable AI/ML models and algorithms to support various business and product requirements. Apply advanced machine learning, natural language processing (NLP), computer vision, or reinforcement learning techniques to address complex challenges. Perform data preprocessing, feature engineering, and exploratory data analysis to ensure high-quality datasets for model training. Optimize machine learning models for accuracy, efficiency, and performance in production environments. Collaborate with cross-functional teams including data scientists, software engineers, and product managers to deliver end-to-end AI solutions. Implement MLOps best practices for versioning, monitoring, retraining, and deploying models in production. Conduct research and stay updated on the latest developments in AI/ML technologies, frameworks, and industry trends. Build proof-of-concepts (POCs) to evaluate new approaches and demonstrate AI capabilities for business use cases. Document solutions, methodologies, and best practices for reusability and knowledge sharing within the team. Ensure ethical and responsible use of AI by incorporating fairness, transparency, and explainability into solutions. Key Skills & Competencies Strong programming skills in Python (mandatory) and familiarity with libraries such as TensorFlow, PyTorch, scikit-learn, Keras, OpenCV, NLTK, or Hugging Face Transformers. Experience with machine learning algorithms, deep learning architectures (CNNs, RNNs, Transformers, GANs), and NLP techniques. Solid understanding of data structures, algorithms, probability, and statistics as applied to AI solutions. Proficiency in working with large datasets, data pipelines, and data preprocessing techniques. Hands-on experience with cloud platforms (AWS, Azure, or GCP) and AI/ML services (e.g., SageMaker, Vertex AI). Knowledge of MLOps practices including model deployment, monitoring, CI/CD, and containerization using Docker and Kubernetes. Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG) approaches for advanced AI solutions. Experience integrating AI models into production systems, APIs, or enterprise applications. Strong problem-solving mindset with the ability to translate business requirements into technical AI solutions. Excellent communication and collaboration skills to work with diverse teams and stakeholders. Qualifications Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. 4–8 years of proven experience in designing and deploying AI/ML solutions in real-world applications. Track record of successfully delivering AI projects end-to-end, from data collection to production deployment.

Responsibilities

Design, develop, and deploy scalable AI/ML models and algorithms to support various business and product requirements. Collaborate with cross-functional teams to deliver end-to-end AI solutions.