Usage of Conventional AI
Virtusa utilizes Artificial Intelligence (AI) technology for the purpose of conducting candidate pre-employment assessments. This AI may include both text-based and voice-based functionalities. The AI technology will have access to the data that you upload or provide during your interaction with the AI bot and will use such data solely for the purpose of performing assessment in accordance with Virtusa policies and practices. The AI is not used to substantially assist or replace discretionary employment decisions. Read our full employee privacy policy here.
Job description
Develop solutions related to data architecture, Mi Platform as well as GenAl platform architect, provide tactical solution and design support to the team and embedded with engineering on the execution and implementation of processes and procedures Serve as a subject matter expert on a wide range of ML. techniques and optimirations
Provide in-depth knowledge of distributed Ml. platform deployment including training and serving Create curative solutions using GenAl workflows through advanced proficiency in large language models (LLM) and related techniques.
Gain Experience with creating a Generative Al evaluation and feedback loop for GenAl/ML, pipelines.
Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team.
Own end to end code development in python/lava for both proof of concept/experimentation and production ready solutions
Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks and collaborate with product and engineering teams to deliver tailored science and technology-driven solutions.
Drives decisions that influence the product design, application functionality, and technical operations and processes
Required Qualifications, Capabilities, and Skills
4+ years of experience in building and deploying ML solutions (Deep learning/ LLMs)
In-depth understanding of classical ML. techniques, deep learning, graph networks, RAGs (and different flavours of KAG, and their applications to structured and unstructured datasets
Good understanding of frameworks such as PyTorch or TensorFlow.
In-depth understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods
Hands-on experience in building and deploying either one of these two-deep leaming models or LLM based solutions
Strong mathematical foundations on how the models work
Expertise in development Deep learning/ LLMs
In-depth understanding of classical ML. techniques, deep learning, graph networks, RAGs (and different flavours of KAG, and their applications to structured and unstructured datasets
Hands-on experience in building and deploying either one of these two-deep leaming models or LLM based solutionsStrong mathematical foundations on how the models work
Qualification
Develop solutions related to data architecture, Mi Platform as well as GenAl platform architect, provide tactical solution and design support to the team and embedded with engineering on the execution and implementation of processes and procedures Serve as a subject matter expert on a wide range of ML. techniques and optimirations
Provide in-depth knowledge of distributed Ml. platform deployment including training and serving Create curative solutions using GenAl workflows through advanced proficiency in large language models (LLM) and related techniques.
Gain Experience with creating a Generative Al evaluation and feedback loop for GenAl/ML, pipelines.
Get Hands on code and design to bring the experimental results into production solutions by collaborating with engineering team.
Own end to end code development in python/lava for both proof of concept/experimentation and production ready solutions
Optimize system accuracy and performance by identifying and resolving inefficiencies and bottlenecks and collaborate with product and engineering teams to deliver tailored science and technology-driven solutions.
Drives decisions that influence the product design, application functionality, and technical operations and processes
Required Qualifications, Capabilities, and Skills
4+ years of experience in building and deploying ML solutions (Deep learning/ LLMs)
In-depth understanding of classical ML. techniques, deep learning, graph networks, RAGs (and different flavours of KAG, and their applications to structured and unstructured datasets
Good understanding of frameworks such as PyTorch or TensorFlow.
In-depth understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods
Hands-on experience in building and deploying either one of these two-deep leaming models or LLM based solutions
Strong mathematical foundations on how the models work
Expertise in development Deep learning/ LLMs
In-depth understanding of classical ML. techniques, deep learning, graph networks, RAGs (and different flavours of KAG, and their applications to structured and unstructured datasets
Hands-on experience in building and deploying either one of these two-deep leaming models or LLM based solutionsStrong mathematical foundations on how the models work
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 30,000 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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