Machine Learning Engineer
1 week ago
AI
, a Fractal company, enables interconnected and automated decisions at the intersection of demand and supply.
By changing how decisions are made, unlocks growth and transforms organizations into adaptive, intelligent enterprises.
Through its 'autonomic decisioning' platform, works with data to provide proactive, interconnected, and automated decisions that help customers reach their true potential – from optimizing workflows to growing the bottom line.
Role Name:
Sr Data Scientist/Lead Data Scientist
Location:
Bangalore | Hybrid
Reporting to:
Director Data Science
No.
of direct reports:
NA/Senior Individual contributor role
Why work with us?
- Experience a fast paced, growing, and stable start-up with a culture of care at heart. You will be enabled to be your best every day – personally & professionally.
- Be a part of the AI revolution and bring to life solutions that make a difference to the world .
- Coming to work will not feel monotonous – you get to work with some of the brightest and the nicest colleagues you will meet and build bonds for life.
- Build for impact at scale with products that will fundamentally transform how CPG operates today and define for tomorrow.
Our Ethos:
Technology cannot do extraordinary things; it is people that make it happen.
Our culture fosters collaboration, continuous learning, innovation, and an agile approach.
A truly inspiring environment that lets you thrive personally and professionally
Why us
At Asper we are on a mission to empower enterprises leveraging AI to grow faster and sustainably at an accelerated pace.
By providing transparent, autonomous, efficient, and interconnected supply chain solutions, we enable businesses to efficiently respond to market shifts, reduce losses and wastages, and offer affordable consumer products.
If you believe that AI can play a pivotal role in transforming traditional industries such as Consumer Packaged Goods (CPG) and supply chain management for the better, join us to become a change-maker.
What will you doAs a Senior/Lead Machine Learning Engineering, you will play a pivotal role in designing, implementing, and maintaining advanced AI/ML systems.
Collaborating closely with data scientists and cross-functional teams, you will ensure the development of robust and scalable machine learning models and workflows that drive our business objectives.
Key Responsibilities:
Model Development and Deployment:
Design, implement, and productionize machine learning models by collaborating closely with scientists and other stakeholders.
Develop, test, and deploy end-to-end ML pipelines for data preparation, training, validation, and monitoring.
System and Workflow Design:
Create comprehensive workflows and architectures for ML (including but not limited to multivariate forecasting)/LLM systems, ensuring high-quality design and scalability.
Technical Leadership:
Provide technical expertise and guidance on performance optimization, large-scale distributed system scalability, and system architecture.
Offer thought leadership in selecting, defining, training, and fine-tuning Large Language Models (LLMs) and other Gen AI efforts.
Tool Utilization:
Leverage ML development and MLOps tools (open-source and cloud enables) to accelerate the speed and efficiency of ML pipelines.
Quality Assurance:
Ensure high standards of quality in AI/ML systems by developing rigorous testing, validation, and monitoring processes.
Implement best practices for code quality, version control, and continuous integration/continuous deployment (CI/CD).
Collaboration and Communication:
Work closely with data scientists, engineers, and business stakeholders to understand complex data flows and application requirements.
Bridge the gap between technical and business requirements to deliver solutions that meet organizational needs.
Innovation and Efficiency:
Identify and integrate state-of-the-art models and solutions to enhance capabilities, drive down technical debt, and increase operational efficiency.
Stay updated with the latest advancements in AI/ML and propose innovative approaches to improve our technology stack.
Qualifications:
Education and Experience:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
5-8 years of experience in machine learning engineering or a related role, preferably in an AI product company.
Technical Skills:
Proficiency in programming languages such as Python or Scala.
Experience with machine learning frameworks and libraries (e.g., Tensor Flow, Py Torch, scikit-learn, and others).
Strong understanding of data structures, algorithms, and software design principles.
Familiarity with cloud services (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
Soft Skills:
Detail-oriented with a strong focus on quality and accuracy.
Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
Strong communication skills, capable of articulating complex technical concepts to non-technical stakeholders.
Preferred
Qualifications:
Experience with large-scale distributed systems and big data technologies (e.g., Hadoop, Spark).
Knowledge of natural language processing (NLP) and experience with Large Language Models (LLMs).
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