Posted on: 17/05/2025
Overview :
- Develop, test, and implement machine learning and generative AI models to drive intelligent decision making and automation.
- Work closely with engineering teams to integrate machine learning models into production systems using microservices architectures.
- Design and develop APIs to enable seamless communication between data models and applications.
- Build and maintain scalable data pipelines to facilitate data collection, transformation, and storage for model training and inference.
- Utilize Python and relevant libraries (e.g., Pandas, NumPy, TensorFlow, PyTorch) to preprocess data, train models, and perform statistical analysis.
- Collaborate with product and business teams to understand requirements and deploy machine learning solutions that meet business needs.
- Perform continuous monitoring, testing, and optimization of deployed models to ensure high performance and reliability.
- Stay updated on the latest trends and advancements in machine learning, generative AI, and related fields to apply cutting-edge techniques in your work.
- Document processes, methodologies, and model outputs for transparency and future improvements.
Required Skills & Qualifications :
- Proven experience in Python programming, including the use of libraries such as Pandas, NumPy, Scikit learn, TensorFlow, PyTorch, or Keras for machine learning.
- Hands-on experience with microservices architecture and containerization technologies like Docker or
Kubernetes.
- Experience with building and deploying APIs to enable machine learning models to interact with other systems and applications.
- Strong understanding of Machine Learning algorithms, including supervised and unsupervised learning, deep learning, and generative AI techniques such as GANs (Generative Adversarial Networks) and language models.
- Ability to work with cloud platforms (AWS, GCP, or Azure) for model deployment and scalability.
- Knowledge of data engineering concepts, including data wrangling, ETL processes, and working with distributed systems.
- Familiarity with modern version control systems (e.g., Git) and agile development practices.
- Strong analytical and problem-solving skills with the ability to communicate complex technical concepts to non-technical stakeholders.
- Experience with data visualization tools (e.g., Tableau, Power BI, or Matplotlib) is a plus.
Preferred Qualifications :
- Knowledge of DevOps practices and CI/CD pipelines for machine learning deployment.
- Familiarity with the integration of ML models into business applications and customer-facing products.
- Strong communication skills and the ability to collaborate with cross-functional teams including engineers, product managers, and business stakeholders
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Posted By
Indu
Talent Acquisition at MINDTEL GLOBAL PRIVATE LIMITED
Last Login: NA as recruiter has posted this job through third party tool.
Posted in
AI/ML
Functional Area
Data Science
Job Code
1481263
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