Machine Learning Engineer
2 weeks ago
About Cognida.ai
Our Purpose is to boost your competitive advantage using AI and Analytics.
We Deliver tangible business impact with data-driven insights powered by AI. Drive revenue growth, increase profitability and improve operational efficiencies.
We Are technologists with keen business acumen - Forever curious, always on the front lines of technological advancements. Applying our latest learnings, and tools to solve your everyday business challenges.
We Believe the power of AI should not be the exclusive preserve of the few. Every business, regardless of its size or sector deserves the opportunity to harness the power of AI to make better decisions and drive business value.
We See a world where our AI and Analytics solutions democratise decision intelligence for all businesses. With Cognida.ai, our motto is ‘No enterprise left behind’.
About the job
Machine Learning Engineer
Location: Hyderabad
Experience: 6+
Role & Responsibilities:
- Design and develop machine learning algorithms and deep learning applications and systems.
- Solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks.
- Analyse complex datasets to uncover insights and patterns that help model development.
Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications.
Identify differences in data distribution that could potentially affect model performance in real-world applications.
Ensure algorithms generate accurate user recommendations.
Implement and test various search and recommendation algorithms to improve system performance.
Optimise existing machine learning models for performance and scalability.
Study and transform data science prototypes and apply appropriate machine learning algorithms and tools.
Extend existing machine learning libraries and frameworks.
Qualifications:
- AI/ML Engineer with 6+ years of experience.
- Should have worked in Generative AI, building annotations, models.
- Extensive math and computer skills, with a deep understanding of probability, statistics, and algorithms.
- In-depth knowledge of machine learning frameworks, like Keras or PyTorch.
- Familiarity with data structures, data modelling, and software architecture.
- Familiarity with Python, Java, and R
- Excellent communication and collaboration skills
- Ability to work with cross functional & client managers.
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