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Open nowPosted 5 days ago

AI/ML Engineer

Workable (global search)108,016 open roles

Where
Pune, MH, India
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Your applicationOpen nowAI/ML EngineerWorkable (global search) · Pune, MH, India

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The clock on this job

Early applications get read.

7.9% of postings close within 7 days. Measured by our own scanner across the market. Workable (global search) postings stay open a median of 7 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 7.9%7 days
  4. 14.9%14 days
  5. 34.0%30 days
This job: posted 5 days ago

Workable (global search) median: 7 days open

The posting

This role is for one of Weekday’s clients Salary range: Rs 500000 - Rs 2700000 (ie INR 5 - 27 LPA)

Min Experience: 6+ years Location: Pune, Maharashtra, India JobType: full-time

We are looking for an experienced and highly skilled AI/ML Engineer with 6–10 years of hands-on experience in Artificial Intelligence, Machine Learning, and Data Science. The ideal candidate will be responsible for designing, developing, deploying, and optimizing intelligent systems and machine learning solutions that solve complex business problems.

You will work closely with data scientists, software engineers, product teams, and business stakeholders to transform data into scalable AI-driven products and actionable insights. The role requires strong technical expertise, problem-solving ability, and experience taking machine learning models from experimentation through production.

Requirements

Key Responsibilities

  • Design, develop, and implement machine learning and AI models for real-world business applications.
  • Analyze large and complex datasets to identify patterns, trends, correlations, and opportunities for predictive modeling.
  • Develop and optimize supervised, unsupervised, and semi-supervised machine learning algorithms.
  • Build end-to-end ML pipelines, including data preparation, feature engineering, model development, validation, deployment, and monitoring.
  • Apply statistical methods and data science techniques to solve business and technical problems.
  • Evaluate model performance using appropriate metrics and continuously improve accuracy, scalability, and efficiency.
  • Work with structured and unstructured data, including text, images, and other high-dimensional datasets.
  • Collaborate with engineering teams to integrate AI/ML models into production applications and APIs.
  • Develop scalable solutions using cloud platforms, distributed computing frameworks, and modern ML infrastructure.
  • Stay updated with advancements in AI, Generative AI, deep learning, NLP, computer vision, and MLOps.
  • Conduct experiments, proof-of-concepts, and technical evaluations for emerging AI/ML technologies.
  • Document model architectures, methodologies, experiments, results, and deployment processes.

Must-Have Skills

  • AI: Strong understanding of Artificial Intelligence concepts, algorithms, and practical applications.
  • Machine Learning: Deep hands-on experience with machine learning algorithms, model development, optimization, and deployment.
  • Data Science: Strong expertise in data analysis, statistical modeling, data preprocessing, feature engineering, and exploratory data analysis.
  • Strong programming skills in Python and familiarity with libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
  • Experience developing and deploying production-grade machine learning models.
  • Strong understanding of model evaluation, validation, feature selection, hyperparameter tuning, and optimization.
  • Experience working with SQL and large datasets.
  • Good understanding of data structures, algorithms, and software engineering principles.
  • Experience with cloud environments such as AWS, Azure, or GCP.
  • Strong analytical, problem-solving, and communication skills.

Good to Have

  • Experience with Generative AI, LLMs, NLP, or Computer Vision.
  • Knowledge of MLOps, model monitoring, CI/CD, Docker, Kubernetes, or MLflow.
  • Experience with distributed data processing technologies such as Spark.
  • Familiarity with vector databases, embeddings, RAG architectures, and AI application development.
  • Experience deploying scalable AI/ML services in production.

Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related field.
  • 6–10 years of relevant professional experience in AI/ML, Machine Learning Engineering, or Data Science.
  • Demonstrated experience building and deploying AI/ML solutions in production environments.
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