
AI/ML Engineer
4 weeks ago
Job Summary :
In this role, you will be responsible for designing, developing, deploying, and maintaining machine learning and artificial intelligence models that power intelligent applications.
Youll work on problems involving prediction, automation, personalization, NLP, computer vision, and more - helping drive data-driven innovation across the organization.
This is a hands-on role that requires both strong software engineering fundamentals and deep knowledge of machine learning techniques.
Key Responsibilities :
- Use libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost for model development.
- Conduct feature engineering, data preprocessing, hyperparameter tuning, and model validation.
- Deploy ML models to production environments using APIs, containers (Docker), or cloud services like AWS SageMaker, Azure ML, or GCP AI Platform.
- Collaborate with software engineers and DevOps teams to integrate models into applications and ensure high availability and scalability.
- Work with structured and unstructured datasets from databases, APIs, or data lakes.
- Perform data cleaning, transformation, normalization, and exploratory data analysis (EDA) to extract insights and improve model accuracy.
- Monitor model performance post-deployment to detect drift or degradation.
- Build tools and processes to retrain, update, and version-control models.
- Document model behavior, performance metrics, and decisions for auditability.
- Translate complex business problems into ML/AI solutions.
- Communicate findings and recommendations to both technical and non-technical stakeholders.
- Stay updated with the latest research, tools, and best practices in Skills & Qualifications :
- 2 - 5+ years of hands-on experience in AI/ML or Data Science roles.
- Proficiency in Python, including libraries like NumPy, pandas, scikit-learn, matplotlib, etc.- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Keras, XGBoost).
- Strong understanding of data structures, algorithms, probability, statistics, and ML algorithms.
- Experience with model deployment and serving (e.g., Flask APIs, FastAPI, SageMaker, Docker,
Kubernetes).
- Familiarity with SQL and/or NoSQL databases.
- Experience with cloud services (AWS, GCP, or Azure) and MLOps tools is a plus
(ref:hirist.tech)-
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