Lead Aiml Engineer

Posted 24 Days Ago
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Bengaluru, Bengaluru Urban, Karnataka, IND
In-Office
5M-6M Annually
Senior level
Artificial Intelligence • HR Tech • Professional Services • Software
The Role
Lead design, development, deployment, and monitoring of enterprise-scale AI/ML solutions. Build scalable ML pipelines, implement forecasting/recommendation/anomaly-detection models, establish MLOps and CI/CD, integrate models with applications, ensure model governance and reliability, mentor data science teams, and drive adoption of LLMs, RAG, and generative AI to deliver measurable business value.
Summary Generated by Built In

This role is for one of the Weekday's clients

Salary range: Rs 5000000 - Rs 6000000 (ie INR 50-60 LPA)

Experience: 8+ yrs

Location: Bengaluru

Job Type: full-time

We are seeking an experienced Lead AI Engineer / Lead Data Scientist to lead the design, development, deployment, and optimization of enterprise-scale AI and Machine Learning solutions. This role combines deep technical expertise with leadership responsibilities, enabling the successful delivery of advanced analytics, predictive modeling, and AI-driven products that create measurable business impact.

You will work closely with product, engineering, data, and business teams to transform complex business challenges into scalable AI solutions. The ideal candidate is passionate about building production-grade machine learning systems, driving AI innovation, and establishing best practices across the AI lifecycle, from experimentation to deployment and monitoring.


RequirementsKey Responsibilities
  • Lead the end-to-end development of Machine Learning and AI solutions, including model design, training, validation, deployment, and monitoring.
  • Build scalable and reusable ML pipelines for data preparation, feature engineering, model training, evaluation, and production deployment.
  • Translate business requirements into effective AI strategies, predictive models, and deployment roadmaps.
  • Design and implement advanced analytics solutions such as forecasting, recommendation systems, anomaly detection, classification models, and optimization engines.
  • Collaborate with Data Engineers and Software Engineers to integrate AI models into business applications, APIs, and operational workflows.
  • Establish and manage MLOps practices, including experiment tracking, model versioning, CI/CD pipelines, automated deployments, monitoring, drift detection, retraining, and rollback strategies.
  • Ensure model reliability, scalability, explainability, and governance while maintaining high standards for quality and compliance.
  • Monitor production systems for performance, accuracy, latency, and business outcomes, driving continuous improvement initiatives.
  • Mentor and guide Data Scientists and ML Engineers, promoting technical excellence and knowledge sharing.
  • Contribute to AI platform architecture decisions and help define enterprise-wide standards for machine learning development and deployment.
  • Drive innovation through the adoption of emerging AI technologies, including Generative AI, LLMs, Retrieval-Augmented Generation (RAG), and advanced analytics frameworks.
What Makes You a Great Fit
  • 8+ years of experience in Data Science, Machine Learning, Applied AI, or Advanced Analytics with proven success in delivering production-grade AI solutions.
  • Strong expertise in machine learning algorithms, feature engineering, model evaluation, tuning, and performance optimization.
  • Advanced programming skills in Python and hands-on experience with frameworks such as Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, PyTorch, and TensorFlow.
  • Extensive experience building and managing end-to-end ML pipelines and scalable AI applications.
  • Strong understanding of MLOps practices, model lifecycle management, CI/CD automation, and cloud-native AI deployment.
  • Experience with cloud platforms, containerization technologies, orchestration tools, and modern DevOps workflows.
  • Deep knowledge of SQL, APIs, feature stores, model registries, monitoring frameworks, and data engineering concepts.
  • Familiarity with Large Language Models (LLMs), Generative AI, embeddings, RAG architectures, and AI-powered business applications.
  • Strong analytical thinking, problem-solving capabilities, and ability to influence technical and business stakeholders.
  • Proven leadership experience mentoring teams, driving AI initiatives, and delivering measurable business outcomes.
  • Excellent communication, stakeholder management, and cross-functional collaboration skills.
  • Ability to thrive in fast-paced environments while balancing strategic planning with hands-on technical execution.

Skills Required

  • 8+ years experience in Data Science, Machine Learning, Applied AI, or Advanced Analytics
  • Strong expertise in machine learning algorithms, feature engineering, model evaluation, tuning, and performance optimization
  • Advanced programming skills in Python
  • Hands-on experience with Scikit-learn, Pandas, NumPy, XGBoost, LightGBM, PyTorch, and TensorFlow
  • Extensive experience building and managing end-to-end ML pipelines and scalable AI applications
  • Strong understanding of MLOps practices, model lifecycle management, and CI/CD automation
  • Experience with cloud platforms
  • Experience with containerization technologies
  • Experience with orchestration tools
  • Deep knowledge of SQL
  • Experience integrating models with APIs and operational workflows
  • Experience with feature stores and model registries
  • Experience with monitoring frameworks, drift detection, retraining, and production monitoring
  • Familiarity with Large Language Models, Generative AI, embeddings, and RAG architectures
  • Proven leadership experience mentoring teams and driving AI initiatives
  • Excellent communication, stakeholder management, and cross-functional collaboration skills
Am I A Good Fit?
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The Company
Year Founded: 2021

What We Do

Weekday is an AI-powered recruitment platform that helps startups hire top-tier engineering and product talent. By leveraging a massive database of white-collar professionals and advanced outreach tools, the company streamlines the hiring process through automated sourcing, AI-driven resume screening, and white-glove contingency services. Their mission is to modernize recruitment by enabling companies to discover and engage passive candidates efficiently, ensuring high-quality hires for critical roles.

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