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Lead Software Engineer- ML

Techvariable -
Guwahati, Assam

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Job details

Full-time

Qualifications

TensorFlow
Azure
Doctoral degree
Computer Science
Kubernetes
Data structures
Spark
System design
Master's degree
AWS
Docker
Bachelor's degree
Machine learning
Kafka
AI
Communication skills
Hadoop
Information Technology

Full job description

Full Time

Guwahati & Bangalore

Experience -

10+ years

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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