Artificial Intelligence/Machine Learning Engineer

4 weeks ago


Pune, Maharashtra, India VINTAGE CONSULTANCY Full time

Key Responsibilities :

- Model Development : Design, develop, train, and evaluate machine learning models (e.g., classification, regression, clustering, NLP, computer vision, time series) to address specific business problems.

- Data Preparation : Work with large, complex datasets, including data collection, cleaning, preprocessing, feature engineering, and validation to ensure high-quality input for models.

- Algorithm Implementation : Implement and experiment with various ML algorithms and techniques, selecting the most appropriate ones for given tasks.

- Deployment & Integration : Assist in deploying ML models into production environments, ensuring scalability, reliability, and performance. Integrate models with existing software systems and APIs.

- Monitoring & Optimization : Monitor deployed models for performance degradation, troubleshoot issues, and continuously optimize models for accuracy, efficiency, and resource utilization.

- Experimentation : Design and execute experiments to test model hypotheses, compare different approaches, and iterate on solutions based on empirical results.

- Research & Learning : Stay updated with the latest advancements in AI/ML research, tools, and best practices. Apply new knowledge to improve existing solutions and explore new opportunities.

- Collaboration : Work closely with data scientists, software engineers, product managers, and other stakeholders to understand requirements, translate them into technical solutions, and integrate AI/ML capabilities Skills & Qualifications :

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.

- 2+ years of hands-on professional experience as an AI/ML Engineer or a similar role.

- Strong proficiency in Python and popular ML/deep learning libraries (e.g., TensorFlow, PyTorch, scikit-learn, Pandas, NumPy).

- Solid understanding of core machine learning concepts, algorithms, and statistical methods.

- Experience with data manipulation, cleaning, and feature engineering.

- Familiarity with building and consuming APIs for model integration.

- Experience with version control systems (e.g., Git).

- Excellent problem-solving, analytical, and debugging skills.

- Good communication (written and verbal) and collaboration Skills (Good to have) :

- Experience with cloud platforms and their ML services (e.g., AWS SageMaker, Google AI Platform, Azure ML).

- Familiarity with MLOps practices, including model versioning, deployment pipelines, and monitoring tools.

- Knowledge of specific domains like Natural Language Processing (NLP) or Computer Vision, if relevant to the company's products.

- Experience with big data technologies (e.g., Spark, Hadoop)

(ref:hirist.tech)

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