Position:
Machine Learning Engineer
Company:
Giggso
Location:
Chennai, Tamil Nadu, India
Job Type:
Full-time
Job Mode:
Hybrid
Job Requisition ID:
Not specified
Years of Experience:
Not explicitly mentioned, but as per JD looks like an entry level job (0-3 years)
Company Description:
Founded in 2018, Giggso is a leading platform dedicated to responsible AI for enterprise operations. It specializes in providing a unified solution for AI agent orchestration, governance, monitoring, observability, incident management, automation, and remediation.
Giggso’s platform integrates cutting-edge web 3.0 and blockchain technologies to ensure robust Model Risk Management solutions.
The company’s mission is to enhance decision-making processes and drive operational efficiency in AI and machine learning (ML) systems.
By focusing on improving customer experiences and managing costs effectively, Giggso empowers enterprises to handle complex AI and ML challenges.
Giggso caters to data science teams, engineering professionals, and business executives by consolidating and acting on diverse information streams ranging from data quality metrics to monitoring bias and drift in AI systems.
The platform emphasizes compliance, audit readiness, and security, ensuring that AI models adhere to enterprise-grade standards.
Benefits of Giggso include reduced operational costs, improved resource utilization, enhanced customer experiences, streamlined compliance, and the ability to manage complex AI ML systems more effectively.
For more details, visit: www.giggso.com.
Profile Overview:
The Machine Learning Engineer role at Giggso involves developing and optimizing algorithms to improve AI and ML system performance.
Key responsibilities include:
Pattern recognition and neural network development.
Implementing statistical analyses and creating models for AI ML systems.
Collaborating on complex AI projects to enhance operational efficiency and manage risk effectively.
The position requires expertise in both theoretical and applied aspects of machine learning, particularly in areas like natural language processing (NLP), algorithm optimization, and model deployment.
Engineers will contribute to Giggso’s mission by integrating advanced technologies such as web 3.0 and blockchain for AI governance.
The hybrid work setup allows professionals to work from the Chennai office while enjoying flexibility for remote work.
This is an opportunity to be part of a cutting-edge team driving innovation in responsible AI and machine learning solutions for enterprise applications.
Qualifications:
Strong technical skills in pattern recognition, neural networks, and algorithm optimization.
Expertise in:
LLM programming with a strong NLP background.
Python programming and mathematical reasoning.
Statistical analysis techniques and model deployment processes.
Demonstrated experience in:
Developing and optimizing algorithms for AI ML systems.
Designing and implementing neural network models.
Handling model risk management through monitoring and observability tools.
Strong problem-solving and analytical abilities.
Advanced academic qualifications:
Master’s degree in Computer Science, Statistics, or a related field (mandatory).
PhD in a relevant discipline (preferred but not required).
Additional Info:
The role offers an opportunity to work at the forefront of AI technology, contributing to innovations in machine learning and responsible AI practices.
Employees will engage with Giggso’s state-of-the-art platform to solve real-world challenges in AI governance, automation, and incident management.
Benefits include:
Exposure to blockchain and web 3.0 technologies.
Collaboration with a dynamic team of experts in AI and ML.
Flexible work arrangements in a hybrid setup.
Professional growth opportunities in a rapidly evolving tech landscape.
Giggso emphasizes a culture of continuous learning and encourages team members to stay updated with the latest advancements in AI and machine learning technologies.
Joining Giggso means becoming part of a team dedicated to transforming enterprise operations through responsible and efficient AI systems.
Please click here to apply.
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