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        • Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

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          No-code data engineering
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          Enterprise-grade LLM

          Custom, integrated predictive layer.

          Automated data movement for faster time-to-insights.

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          Structured data for reporting, analytics and model training.

        • Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

          Advanced Data ETL, Reporting and Gen AI

          No-code data engineering
          Automated data transformation
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          Visual insights to help you optimize your data for analytics.

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        • Data lifecycle management for seamless source-to-destination data movement, next-gen analytics and AI integration.

          Advanced Data ETL, Reporting and Gen AI

          No-code data engineering
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          Enterprise-grade LLM

          We are a bold team supporting bold leaders like you ready to adopt and migrate to new technologies.

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Job Details

 Lead Software Engineer- ML

Full Time

Guwahati & Bangalore

Experience -

10+ years

Positions -

1

CTC-

Best In Industry

Job Description

We are looking for an accomplished and visionary Lead Software Engineer – Machine Learning to drive the design, development, and deployment of advanced machine learning solutions. This role requires strong leadership, deep technical expertise, and a proven ability to guide teams in solving complex, large-scale problems using cutting-edge ML technologies. As a leader, you will mentor teams, define technical roadmaps, and collaborate across departments to align machine learning initiatives with business objectives.

Roles and Responsibilities

  • Define and lead the strategy and roadmap for ML systems and applications.
  • Architect and oversee the development of scalable machine learning systems and infrastructure.
  • Drive the design and implementation of advanced ML models and algorithms to address complex business problems.
  • Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to identify ML use cases and requirements.
  • Mentor and guide junior and mid-level engineers in best practices for ML development and deployment.
  • Monitor, evaluate, and improve the performance of machine learning systems in production.
  • Ensure compliance with industry standards and best practices for model development, data governance, and MLOps.
  • Lead research initiatives to explore emerging ML techniques and integrate them into the organization’s solutions.

Required Skills

Education: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. A Ph.D. is a plus.

Technical Skills:

  • 10+ years of experience in software engineering, with at least 5 years focusing on machine learning.
  • Proficiency in ML frameworks and libraries like TensorFlow, PyTorch, and scikit-learn.
  • Strong expertise in designing and building large-scale, distributed ML systems.
  • Advanced knowledge of data engineering tools and frameworks, such as Spark, Hadoop, or Kafka.
  • Hands-on experience with cloud platforms (AWS, GCP, Azure) for ML workloads.
  • Expertise in deploying and managing ML models in production environments using MLOps tools like MLflow or Kubeflow.
  • Deep understanding of algorithms, data structures, and system design.
  • Experience with containerization (Docker) and orchestration (Kubernetes).

Experience: 10+ years of experience in data engineering or related fields.

Soft Skills:

  • Strong leadership and decision-making capabilities.
  • Exceptional problem-solving and analytical thinking.
  • Excellent communication skills to convey technical concepts to both technical and non-technical audiences.
  • Ability to foster collaboration and drive innovation across teams.

Preferred Skills/Qualifications

Education: Master’s degree in Computer Science, Information Technology, or related field.

Technical Skills:

  • Familiarity with cutting-edge techniques like generative AI, reinforcement learning, or federated learning.
  • Experience in building and managing real-time data processing pipelines.
  • Knowledge of data security and privacy best practices, particularly in regulated industries.
  • Publications or patents in the field of machine learning or artificial intelligence.

Experience: 10+ years

Key Performance Indicators:

  • Successful delivery of scalable, high-impact ML solutions aligned with business goals.
  • Effective mentorship and upskilling of team members.
  • Continuous improvement of ML system performance and reliability.
  • Innovation and adoption of emerging ML techniques to maintain a competitive edge.

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