Artificial Intelligence Engineer at Weekday AI

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

08 Feb, 26

Salary

0.0

Posted On

10 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Artificial Intelligence, Machine Learning, Deep Learning, Large Language Models, Data Engineering, Algorithm Optimization, Model Deployment, Collaboration, Research, Performance Monitoring, Python, TensorFlow, PyTorch, Natural Language Processing, Cloud AI Platforms, MLOps

Industry

technology;Information and Internet

Description

This role is for one of the Weekday's clients Min Experience: 3 years Location: Gurugram JobType: full-time We are seeking a highly skilled and innovative Artificial Intelligence Engineer with hands-on experience in designing, developing, and deploying AI-driven solutions. The ideal candidate will possess strong expertise in machine learning (ML), deep learning, and large language models (LLMs), with the ability to transform data into actionable intelligence. This role offers the opportunity to work at the cutting edge of AI, building scalable systems that power intelligent automation, predictive analytics, and natural language understanding across business domains. Key Responsibilities AI Model Development: Design, train, and optimize AI and machine learning models, including supervised, unsupervised, and reinforcement learning techniques, to address complex business challenges. Large Language Models: Work extensively with LLMs (e.g., GPT, LLaMA, Claude, or Gemini) — fine-tuning, prompt engineering, and developing applications leveraging transformer-based architectures. Data Engineering & Preparation: Collect, preprocess, and analyze structured and unstructured data to ensure data quality and model performance. Algorithm Optimization: Research and implement advanced algorithms for tasks such as natural language processing (NLP), computer vision, and generative AI, ensuring scalability and efficiency. Model Deployment & Integration: Deploy AI models into production environments using MLOps best practices and ensure seamless integration with existing systems or APIs. Collaboration & Innovation: Work closely with data scientists, software engineers, and product teams to translate business requirements into intelligent and automated solutions. Research & Experimentation: Stay updated on the latest AI advancements, frameworks, and LLM capabilities, experimenting with new architectures and techniques to drive continuous improvement. Performance Monitoring: Develop evaluation metrics and continuously monitor model accuracy, fairness, and bias to maintain ethical and reliable outcomes. Required Skills & Qualifications Education: Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field. Experience: 3–5 years of professional experience in AI and ML model development, with proven contributions to real-world deployments. Technical Proficiency: Strong programming skills in Python and familiarity with TensorFlow, PyTorch, Keras, or similar frameworks. Deep understanding of transformer architectures, embedding models, and language model fine-tuning. Hands-on experience with data processing tools (Pandas, NumPy, scikit-learn) and MLOps pipelines (MLflow, Docker, Kubernetes). Proficiency in natural language processing, predictive analytics, and model evaluation metrics. Exposure to cloud AI platforms (AWS SageMaker, Azure ML, or Google Vertex AI). Preferred Attributes Experience with vector databases (e.g., Pinecone, Weaviate, FAISS) and retrieval-augmented generation (RAG) pipelines. Ability to design prompt engineering strategies and fine-tune LLMs for custom use cases. Strong analytical, problem-solving, and mathematical reasoning skills. Excellent communication and collaboration skills, with a passion for innovation and learning.

Responsibilities

The role involves designing, training, and optimizing AI and machine learning models to address complex business challenges. The candidate will also work on deploying AI models into production environments and collaborating with various teams to create intelligent solutions.