Associate Machine Learning Engineer

Job description

Responsiblities

• Design and develop machine learning and deep learning systems, including the creation of algorithms and AI models to extract valuable insights from large, complex data sets.

• Taking full ownership of projects, leading from the initial understanding of the business problem through to the implementation and monitoring of the solution.

• Deploying and maintaining AI models in production.

• Conduct rigorous machine learning tests and experiments, performing statistical analysis to fine-tune models based on test results.

• Compare results from various methodologies, recommending the most effective techniques to stakeholders and leading improvements in methodology to address capability gaps or increase efficiency.

• Collaborating with senior team members to shape the team's technical vision and participate in code reviews to maintain high-quality standards.

• Leverage the latest advancements in Machine Learning and AI to build, test, and validate predictive models, transforming and converting data science prototypes.

• Troubleshoot data/system issues, maintain technical design and drive continuous improvement within an agile development team, making impactful contributions to discussions on emerging machine learning methodologies.

• Mentoring the junior engineers in the team

Required Skill Sets

• A degree in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science or related quantitative field (Masters or PhD preferred )

• Experience in NLP, showcasing adeptness in both Natural Language Understanding and Generation domains

• Comprehensive knowledge of transformer-based models and large language models, with experience in fine-tuning of the latter.

• Solid understanding of Algorithms and Data Structures

• Good understanding of vector databases, Elastic Search and Neural search

• Experience in fine-tuning of large language models is preferred

• Experience in Computer Vision is a plus

• Experience in prompt engineering of large language model is a plus

• Should be able to understand business problems, identify relevant data, select suitable algorithms, and determine effective production models.

• Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs)

• Good understanding of machine learning pipelines and machine learning frameworks such as TensorFlow and Pytorch and worked on real ML projects that have reached production environment

What can you expect:

• Opportunity to work on interesting and hard research problem, to see real application of state-of-the-art research into practice.

• Opportunity to work on important problem with big social impact: Massive, and direct impact of the work you do on lives of students.

• An intellectually invigorating, phenomenal work environment, with massive ownership and growth opportunities.

• Learn effective engineering habits required to build/deploy large production ready ML applications.

• Ability to do quick iterations and deployments.

Role: Machine Learning Engineer

Industry Type: E-Learning / EdTech

Department: Data Science & Analytics

Employment Type: Full Time, Permanent

Role Category: Data Science & Machine Learning

Education

UG: B.Tech/B.E. in Any Specialization