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Open nowPosted 45 days ago

AI/ML Engineer

uvation94 open roles

Where
India, Remote
Work mode
Remote
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Your applicationOpen nowAI/ML Engineeruvation · India, Remote

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  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 45 days ago

The posting

Job Title: AI/ML Engineer Department: IT Services Reports To: IT Project Manager

Job Overview:

The AI/ML Engineer plays a critical role in designing, developing, and deploying machine learning models and AI-driven solutions to support strategic business initiatives. The role involves collaborating with cross-functional teams, including software engineering, data analytics, product development, and business stakeholders, to drive intelligent automation, data-driven decision-making, and advanced analytics capabilities.

The ideal candidate will have 3 to 5 years of experience in AI/ML model development, with a strong foundation in machine learning algorithms, data preprocessing, and deployment pipelines. Experience with Python, TensorFlow/PyTorch, and cloud-based ML services is essential.

Responsibilities:

1. Model Development and Optimization

  • Design, build, and deploy ML models for classification, regression, NLP, computer vision, or time-series forecasting.
  • Select appropriate algorithms and techniques based on business needs and data characteristics.
  • Continuously monitor and improve model performance using metrics and feedback loops.

2. Data Preparation and Feature Engineering

  • Clean, preprocess, and transform structured and unstructured datasets for training and inference.
  • Engineer and select relevant features to improve model accuracy and generalizability.
  • Collaborate with data engineers to ensure data quality and accessibility.

3. Model Deployment and MLOps

  • Package and deploy models using tools like Docker, Flask/FastAPI, and Kubernetes.
  • Implement CI/CD pipelines for ML using platforms like MLflow, Airflow, or Kubeflow.
  • Monitor deployed models for drift, latency, and performance in production environments.

4. AI Solutions and Use Case Implementation

  • Work with business stakeholders to translate real-world problems into AI/ML use cases.
  • Prototype and test AI-driven solutions (e.g., recommendation engines, chatbots, fraud detection).
  • Contribute to proof-of-concept projects and assist in scaling successful models to production.

5. Research and Innovation

  • Stay updated with the latest research, frameworks, and tools in machine learning and AI.
  • Experiment with cutting-edge models (e.g., LLMs, transformers, generative AI) and assess their viability.
  • Promote innovation by recommending and implementing modern AI strategies.

6. Cross-functional Collaboration

  • Collaborate with software developers, DevOps, data analysts, and domain experts for end-to-end solution delivery.
  • Translate technical insights into business value through clear documentation and presentations.

7. Documentation and Best Practices

  • Maintain comprehensive documentation for models, experiments, and pipelines.
  • Ensure reproducibility, scalability, and compliance with data governance policies.

Requirements:

Experience:

  • 3–5 years of hands-on experience in machine learning model development and deployment.
  • Proven track record of solving real-world problems using supervised, unsupervised, or deep learning methods.

Technical Skills:

Strong knowledge of:

  • Python and ML libraries (scikit-learn, pandas, NumPy, TensorFlow/PyTorch)
  • Model evaluation, hyperparameter tuning, and pipeline automation
  • REST APIs for model serving and integration

Familiarity with:

  • MLOps tools (MLflow, Airflow, DVC, Docker, Kubernetes)
  • Cloud ML services (AWS SageMaker, Azure ML, GCP AI Platform)
  • NLP or computer vision frameworks (e.g., Hugging Face, OpenCV)

Soft Skills:

  • Strong analytical and problem-solving abilities.
  • Excellent communication skills, both verbal and written.
  • Ability to work independently and within cross-functional teams.
  • Curiosity, adaptability, and willingness to learn continuously.
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