Senior AI/ML Engineers ( FDE)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI/ML Engineers (FDE) based in India.

This role offers the opportunity to build, deploy, and maintain practical AI and machine learning solutions for a large global client. You will work across the full AI lifecycle, from data preparation and model development to cloud deployment, optimization, and production support. The position combines machine learning, generative AI, NLP, big data, cloud engineering, and advanced analytics. You will develop scalable solutions using modern frameworks, cloud platforms, and data technologies while solving real-world business challenges. You will also explore Large Language Models and Agentic AI systems that enable more autonomous and intelligent workflows. Working in a collaborative environment, you will have meaningful ownership of technical solutions while continuously expanding your expertise across emerging AI technologies.

Accountabilities:

• Develop, train, deploy, and optimize machine learning models for practical use cases including predictive analytics, classification, clustering, conversational AI, text generation, and summarization.
• Build AI solutions using frameworks such as TensorFlow, PyTorch, and Scikit-learn, applying sound software engineering and machine learning practices.
• Design and implement scalable AI applications across cloud platforms including AWS, Azure, and Google Cloud.
• Develop cloud-native solutions using services such as AWS SageMaker, Lambda, S3, and other application and data services.
• Integrate and fine-tune Hugging Face transformer models, including BERT, GPT, and similar architectures, for NLP use cases such as text classification, sentiment analysis, summarization, and conversational applications.
• Develop AI-powered automation solutions, including chatbot and conversational experiences using technologies such as Microsoft Teams and Azure AI.
• Work with Large Language Models to develop, fine-tune, train, evaluate, and deploy AI applications for conversational and generative use cases.
• Design and implement Agentic AI systems that enable autonomous agents to make decisions, adapt to changing conditions, and optimize tasks dynamically.
• Build and optimize large-scale data processing solutions using Apache Spark and Snowflake.
• Design, implement, and maintain ETL pipelines supporting data transformation, quality management, and analytics.
• Work with SQL and databases including MySQL, PostgreSQL, and MongoDB to manage data and optimize queries.
• Develop interactive data visualizations and analytical dashboards using tools such as Tableau and Power BI to communicate insights effectively.
• Collaborate with customers and internal technical teams to understand requirements, deliver solutions, gather feedback, and continuously improve implementations.
• Apply strong data intuition and quality practices to validate, cleanse, and prepare datasets for reliable analysis and modeling.
• Contribute to continuous improvement of AI solutions, reporting, data processes, model performance, and overall delivery quality.

Requirements

• 3-6 years of professional experience applying AI, machine learning, data science, or related technologies to practical business and technical problems.
• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence/Machine Learning, or a related discipline.
• Strong programming skills in Python and SQL, with hands-on experience using machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Strong understanding of algorithms, object-oriented programming, functional design principles, and software engineering fundamentals.
• Proficiency with data analytics libraries such as Pandas, NumPy, and Matplotlib.
• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud, with the ability to develop and deploy production-ready applications.
• Experience with AWS services such as SageMaker, Lambda, S3, and related cloud infrastructure is highly valuable.
• Experience with big data processing technologies such as Apache Spark and Snowflake.
• Knowledge of NLP, transformer architectures, Hugging Face, Large Language Models, and cloud-based AI services.
• Strong understanding of database management, data modeling, query optimization, and data engineering practices.
• Experience developing ETL/ELT pipelines and working with data quality, transformation, and analytics workflows.
• Experience with Tableau, Power BI, or comparable data visualization platforms.
• Strong analytical and problem-solving skills, with curiosity and enthusiasm for exploring emerging AI technologies.
• Ability to work independently, manage priorities, and adapt effectively to changing project requirements.
• Strong communication and collaboration skills, with the ability to explain technical concepts clearly to different audiences.
• Ability to work effectively in a client-focused, collaborative environment and quickly adapt to new technologies and business contexts.

Benefits

• Full-time opportunity based in India.
• Opportunity to work directly on practical AI/ML solutions supporting a large global client.
• Exposure to a broad and modern technology stack spanning machine learning, Generative AI, LLMs, Agentic AI, NLP, cloud computing, big data, and analytics.
• Hands-on experience with AWS, Azure, and Google Cloud environments and advanced AI services.
• Opportunity to work with technologies including TensorFlow, PyTorch, Scikit-learn, Hugging Face, Apache Spark, Snowflake, SQL, and modern database platforms.
• Exposure to emerging Agentic AI architectures and autonomous AI applications.
• Collaborative environment with opportunities to work alongside customer, engineering, data science, and professional services teams.
• Opportunity to develop expertise across the full AI lifecycle, from data preparation and model development through deployment and optimization.
• Inclusive and diverse workplace focused on respect, collaboration, and continuous learning.
• Compensation and additional benefits are determined by the hiring company and will be discussed during the recruitment process.