Job description
We are seeking an experienced AI / ML Architect to lead the design, development, and implementation of advanced AI and machine learning systems.

The ideal candidate will have a deep technical background in Python and data science libraries, strong expertise in AI and ML algorithms, and hands-on experience in architecting scalable AI solutions.

This role requires a mix of technical proficiency, leadership, and innovative thinking to advance our AI capabilities.

Key Responsibilities :
• Data Preparation & Analysis : Identify, clean, and summarize complex datasets from disparate sources to enable high-quality analyses and insights.
• Scripting & Automation : Develop Python / PySpark scripts for data processing and transformation, leveraging AWS Glue, Lambda, and other serverless architectures.
• Machine Learning Expertise : Apply advanced machine learning techniques including Bayesian methods, time series forecasting, regression, clustering, decision trees, and deep learning algorithms using frameworks like PyTorch and TensorFlow.
• Model Development & Validation : Design and fine-tune machine learning models, ensuring high accuracy and efficiency. Perform robust model validation using state-of-the-art methods.
• Data Engineering : Build efficient data pipelines to process and transform raw data for use in modeling and analytics.
• Distributed Systems Proficiency : Utilize distributed databases and frameworks (Map / Reduce, Hadoop, Hive) for large-scale data processing.
• Advanced ML Libraries : Leverage computational and statistical libraries such as Spark MLlib, Scikit-learn, SciPy, StatsModels, SAS, and R for model development and deployment.
• AI Systems Design : Lead the design and architecture of AI systems with a strong focus on Retrieval-Augmented Generation (RAG) techniques, large language models, and other machine learning algorithms.
• RAG System Implementation : Develop and fine-tune RAG systems to improve the performance and relevance of AI-driven outputs, seamlessly integrating external data sources into generative models.
• Engineering Pipelines : Build and maintain pipelines for model training, evaluation, and deployment, ensuring robust and scalable AI solutions, with emphasis on RAG methodologies.
• Evaluation & Benchmarking : Conduct thorough evaluation and benchmarking of AI models, including RAG systems, to drive data-driven decision-making for model selection.
• Collaboration & Integration : Collaborate with data scientists, engineers, and product managers to integrate AI models into production, ensuring alignment with business goals and seamless operation.
• Innovation & Continuous Learning : Stay updated on the latest advancements in AI and machine learning, particularly in RAG and generative models, and incorporate cutting-edge techniques into the team's practices.
• Documentation & Standards : Develop and maintain documentation for AI systems, ensuring best practices and standards are followed across the organization.
• Mentorship & Leadership : Provide mentorship to junior AI engineers and data scientists, fostering an environment of continuous learning and knowledge sharing.

Qualifications :
• Total Experience 5-7 years with relevant experience in AI / ML is 2-3 years.
• Proficiency in Python and data science libraries like NumPy , SciPy , Pandas , and Scikit-learn .
• Hands-on experience with PySpark scripting and AWS services such as Glue and Lambda .
• Strong knowledge of Bayesian methods and time series forecasting .
• Expertise in machine learning algorithms , model validation, and deep learning frameworks like PyTorch and TensorFlow .
• Experience in handling structured, unstructured , and semi-structured data .
• Advanced knowledge of distributed databases such as Map / Reduce , Hadoop , Hive .
• Familiarity with RAG systems and large language models for AI-driven outputs.
• Experience with supervised and unsupervised learning techniques, including forecasting, classification, text mining, NLP, and search algorithms.
• Strong collaboration, leadership, and mentorship skills.

Preferred Experience :
• Experience working with Spark MLlib , SciPy , StatsModels , SAS , and R .
• Proven track record in developing and fine-tuning RAG systems for enhancing AI outputs.
• Ability to innovate and apply the latest AI techniques to real-world business problems.

About Us :

TechAhead is a global digital transformation company with a strong presence in both the USA and India, specializing in AI-first product design thinking and bespoke development solutions.

With over 14 years of proven expertise, we have partnered with Fortune 500 companies and leading global brands to drive digital innovation and deliver excellence.

At TechAhead, you’ll be part of a dynamic, forward-thinking team that values continuous learning, growth, and crafting tailored solutions to meet the unique needs of our clients.

Join us in shaping the future of digital innovation across the world!