Proficient in Python with a focus on machine learning and datascience experience
1. Strong Python Expertise: Proven experience in developing, optimizing, and scaling Python-based applications, with a focus on implementing complex algorithms and handling large datasets. Must be proficient in working with popular Python libraries such as NumPy, TensorFlow, PyTorch, and Scikit-learn.
2. Research Paper Interpretation & Implementation: Ability to read and understand academic research papers, implement the proposed algorithms or models in Python, and demonstrate their functionality through well-documented code and reproducible experiments.
3. Experience in Generative AI: Hands-on experience in developing and fine-tuning generative AI models (e.g., GANs, VAEs, transformers). Experience with state-of-the-art generative models is a plus.
4. Open Source Contributions: Proven track record of contributing to open-source projects, with a preference for contributions in AI or machine learning-related projects. Familiarity with Git and collaboration tools for distributed software development.
5. Problem-Solving & Communication Skills: Strong analytical and problem-solving abilities with the capacity to present complex technical solutions clearly. Ability to work closely with cross-functional teams, including data scientists, product managers, and researchers.
* Experience with NLP concepts.
* Hands-on experience with data preprocessing, feature engineering, and model evaluation using Pandas, Numpy, and Scikit-learn
* Experience designing mission-critical, highly available enterprise applications
* Implement end-to-end LLM security risk management processes and automated protections
* Support production deployments of AI/ML safety systems using cloud-native packaging and deployment techniques like containers, serverless, CI/CD, and APIs
* Deliver and integrate AI robustness, vulnerability, and stress testing capabilities with MLOps ecosystems
* Provide production support and operations for AI/ML security systems
* Manage cloud deployments and automation frameworks in cloud for AI/ML security systems
* Establish and govern AI/ML and Generative AI application security standards
* Strong interpersonal communication skills and ability to work well in a diverse team-focused environment.
skill
Python
NumPy, TensorFlow, PyTorch, and Scikit-learn
Gen AI Models
Git
Proficient in Python with a focus on machine learning and datascience experience
1. Strong Python Expertise: Proven experience in developing, optimizing, and scaling Python-based applications, with a focus on implementing complex algorithms and handling large datasets. Must be proficient in working with popular Python libraries such as NumPy, TensorFlow, PyTorch, and Scikit-learn.
2. Research Paper Interpretation & Implementation: Ability to read and understand academic research papers, implement the proposed algorithms or models in Python, and demonstrate their functionality through well-documented code and reproducible experiments.
3. Experience in Generative AI: Hands-on experience in developing and fine-tuning generative AI models (e.g., GANs, VAEs, transformers). Experience with state-of-the-art generative models is a plus.
4. Open Source Contributions: Proven track record of contributing to open-source projects, with a preference for contributions in AI or machine learning-related projects. Familiarity with Git and collaboration tools for distributed software development.
5. Problem-Solving & Communication Skills: Strong analytical and problem-solving abilities with the capacity to present complex technical solutions clearly. Ability to work closely with cross-functional teams, including data scientists, product managers, and researchers.
* Experience with NLP concepts.
* Hands-on experience with data preprocessing, feature engineering, and model evaluation using Pandas, Numpy, and Scikit-learn
* Experience designing mission-critical, highly available enterprise applications
* Implement end-to-end LLM security risk management processes and automated protections
* Support production deployments of AI/ML safety systems using cloud-native packaging and deployment techniques like containers, serverless, CI/CD, and APIs
* Deliver and integrate AI robustness, vulnerability, and stress testing capabilities with MLOps ecosystems
* Provide production support and operations for AI/ML security systems
* Manage cloud deployments and automation frameworks in cloud for AI/ML security systems
* Establish and govern AI/ML and Generative AI application security standards
* Strong interpersonal communication skills and ability to work well in a diverse team-focused environment.
skill
Python
NumPy, TensorFlow, PyTorch, and Scikit-learn
Gen AI Models
Git
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 36,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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