Data Scientist - NLP/Computer Vision

Job Title : AI/ML Engineer (Data Scientist)

Location : Bangalore

Job Description :

We are an innovative technology company committed to driving business transformation through AI and Machine Learning solutions. We specialize in solving complex business challenges by leveraging cutting-edge AI/ML technologies, delivering scalable, reliable, and maintainable solutions for our clients. We are looking for a skilled AI/ML Engineer to join our dynamic team and play a crucial role in building production-grade AI/ML pipelines and solutions.

Job Description :

As an AI/ML Engineer, you will be responsible for designing, developing, and deploying AI and ML models to address complex business challenges. You will collaborate with cross-functional teams, including Data Engineers and Data Scientists, to build scalable, production-grade AI/ML pipelines. Your work will ensure the deployed models are reliable, maintainable, and optimized for performance in real-world environments.

Responsibilities :

• Design, Develop, and Deploy AI/ML Models : Address complex business challenges through AI and ML solutions, ensuring production-grade deployments.
• Build Scalable AI/ML Pipelines : Work on data preprocessing, feature engineering, model training, validation, deployment, and ongoing monitoring of AI/ML models.
• Collaboration with Cross-functional Teams : Collaborate with Data Engineers, Data Scientists, and other stakeholders to implement end-to-end AI/ML solutions.
• Optimize AI/ML Models in Production : Ensure that deployed models are reliable, scalable, and continuously optimized for high performance in production environments.
• Develop APIs and Microservices : Build APIs or microservices to integrate AI/ML models into business solutions, making them usable across different platforms.
• Implement MLOps Practices : Optimize workflows using CI/CD pipelines, automated retraining of models, version control, and monitoring.
• Apply State-of-the-art AI/ML Techniques : Utilize deep learning, NLP, computer vision, and time-series analysis to develop innovative solutions.
• Ensure Ethical AI Practices : Adhere to data privacy, security, and ethical AI standards throughout the entire lifecycle of AI/ML models.
• Stay Up-to-date with Industry Trends : Continuously explore and implement the latest AI/ML techniques, tools, and best practices.
• Assist in Documentation & Best Practices : Help create and maintain standards, workflows, and documentation for data technology and AI/ML projects.
  
  

Required Skills & Qualifications :

• Strong Expertise in AI/ML Frameworks : Proficiency with TensorFlow, PyTorch, or Scikit-learn for building and deploying models.
• Proficiency in Programming Languages : Strong command of Python or R, including libraries/tools for data science and machine learning.
• Experience with Cloud-based AI/ML Services : Hands-on experience with Microsoft Azure and Databricks.
• MLOps Experience : Expertise in implementing automated pipelines, model versioning, monitoring, and lifecycle management.
• Domain-Specific AI Expertise : Deep knowledge in NLP, computer vision, predictive analytics, or other specialized AI techniques.
• Excellent Problem-Solving Skills : Ability to identify and address technical challenges with innovative and efficient solutions.
• Effective Communication Skills : Strong ability to convey complex technical concepts to both technical and non-technical audiences.
• Attention to Detail : Ability to handle and execute highly specialized projects with a focus on quality.
  
  

Desired Skills & Qualifications :

• Familiarity with Distributed Computing : Knowledge of Apache Spark and scalable training techniques for large datasets.
• Experience with GenAI : Hands-on experience in developing enterprise-level Gen AI applications and models for business use cases.
• Knowledge of Data Privacy & Security Standards : Understanding of ethical AI principles and ensuring compliance with relevant privacy and security standards.
• Interpersonal Skills : Excellent collaboration and relationship-building skills with colleagues, stakeholders, and external partners.
  
  

(ref:hirist.tech)