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AI Developer / Data Scientist

Exclusive opportunity

Onsite

AI Developer / Data Scientist

Awign Enterprises

AI Developer / Data Scientist

Skills

Google Cloud PlatformSQL QueriesDeep LearningDockerFlaskPythonData ScienceNumPypandasPyTorchTensorFlowAWS LambdaMachine LearningAIAWSGitHubNLP / Natural Language ProcessingFastAPI

1 year ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

13 October 2026

What they need


Job highlights

  • Proven hands-on experience in fine-tuning pre-trained models,with particular emphasis on Large Language Models (LLMs) or NLP models . A strong grasp of data preprocessing,feature engineering,and robust model evaluation / optimization techniques
  • Preferred Qualifications: . Bacheloror masterdegree in computer science,Artificial Intelligence,Data Science,or related field

Job_Description":"

Job Title: AI Engineer / Data Scientist

Experience: 5+ Years (Mid-Level)

Job Summary: Were seeking a passionate and skilled AI Engineer / Data Scientist to join our rapidly growing AI & Data Science team. In this pivotal role, youll be at the forefront of designing, developing, and deploying cutting-edge AI models and systems, directly contributing to innovation and business value. This hands-on position requires deep expertise in building and scaling machine learning and deep learning models, with a collaborative spirit to work across various teams.

Key Responsibilities:

  • Develop, train, and evaluate advanced AI/ML models for applications including classification, prediction, NLP, computer vision, and Generative AI.

  • Collaborate closely with data scientists, product managers, and fellow engineers to conceptualize and build impactful AI-powered features and solutions.

  • Construct and refine robust end-to-end ML pipelines, from efficient data ingestion to seamless model deployment in production environments ( MLOps Pipelines)

  • Apply state-of-the-art techniques, including transfer learning, reinforcement learning, and the fine-tuning of pre-trained models, with a strong focus on Large Language Models (LLMs) or Convolutional Neural Networks (CNNs).

  • Deploy and serve models effectively using containerization (Docker), exposing them via performant APIs on leading cloud platforms.

  • Proactively monitor and implement strategies for retraining production models to guarantee sustained performance, reliability, and stability over time.

  • Continuously research and evaluate new AI trends and cutting-edge technologies, actively identifying opportunities to integrate them into our product offerings.

    Required Skill Set:

    • Expert proficiency in Python, coupled with extensive experience using Pandas, NumPy, Scikit-learn, and either TensorFlow or PyTorch.

    • A solid understanding of core machine learning algorithms (supervised and unsupervised) and a deep comprehension of deep learning architectures including CNNs, RNNs, and especially Transformers.

    • Proven hands-on experience in fine-tuning pre-trained models, with particular emphasis on Large Language Models (LLMs) or NLP models

    • A strong grasp of data preprocessing, feature engineering, and robust model evaluation/optimization techniques.

    • Practical experience with model deployment using frameworks like Flask or FastAPI, combined with containerization via Docker.

    • Demonstrated exposure to leading cloud platforms like AWS (e.g., SageMaker, Lambda, S3) or GCP (e.g., Vertex AI, Cloud Run) for building and deploying scalable AI solutions.

    • Knowledge of ETL pipelines, experience working with structured and unstructured data, and proficiency in basic SQL for data querying.

    • Proven ability to thrive both independently and as an integral part of a collaborative team.

      Preferred Qualifications:

      • Bacheloror masterdegree in computer science, Artificial Intelligence, Data Science, or related field.

      • Prior experience in building AI systems in production environments.

      • Publications, personal projects, or GitHub repos showcasing AI work are a plus.

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