| Gen AI Solutions Architectat Remote at Remote, Remote, USA |
| Email: [email protected] |
| From: Sanjay Sunar, convextech [email protected] Reply to: [email protected] Position: Gen AI Solutions Architect Location: Remote Duration: 6+ Months Visa: No H1B/CPT Interview: Video/Skype Job Description: Collaborate with data scientists and other AI professionals to augment digital transformation efforts by identifying and piloting use cases. - Discuss the feasibility of use cases along with architectural design with business teams and translate the vision of business leaders into realistic technical implementation. At the same time, bring attention to misaligned initiatives and impractical use cases. - Align technical implementation with existing and future requirements by gathering inputs from multiple stakeholders business users, data scientists, security professionals, data engineers and analysts, and those in IT operations and developing processes and products based on the inputs. - Play a key role in defining the AI architecture and selecting appropriate technologies from a pool of open-source and commercial offerings. Select cloud, on-premises, or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools. - Audit AI tools and practices across data, models, and software engineering with a focus on continuous improvement. Ensure a feedback mechanism to assess AI services, support model recalibration, and retrain models. - Work closely with security and risk leaders to foresee and overturn risks, such as training data poisoning, AI model theft, and adversarial samples, ensuring ethical AI implementation and restoring trust in AI systems. - Remain acquainted with upcoming regulations and map them to best practices, AI architecture and pipeline planning. - Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across data management, governance, model building, deployment, and production workflows of AI is a must. - Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes, and CI/CD. - Collaborative to ensure that AI platforms deliver both business and technical requirements, seek to collaborate effectively with data scientists, data engineers, data analysts, ML engineers, other architects, business unit leaders, and CxOs (technical and nontechnical personnel), and harmonize the relationships among them. - Lead the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields, including multi-modal capabilities. - Lead MLOps, automating ML pipeline, including the training, testing, deployment, monitoring, and scaling of AI models. Turn prototypes into automation pipelines and deploy them to production; deciding when to use out-of-the-box solutions vs. building custom solutions and utilizing bot h. - Ongoing data analysis to build new or fine-tune existing models such as GPT to optimize results. Partner closely with software engineers to implement these models into high-performing systems and models in our production environment that can be applied to create amazing experiences for our worldwide audience. - Actively engaging in all aspects of model development, from ideation and experimentation to deployment. Communicate results of analyses to business partners and executives. - Maintain expertise in the latest advancements in AI technology. Partner with your business team members to prepare presentations, executive review materials. - Proactively address and reduce potential biases in model predictions, ensuring our products are inclusive and fair. - Design and implement efficient data pipelines to support large language model training and inference. Experience: - A strong track record of shipping products, identifying and delivering state-of-the-art product architecture for our end-to-end solutions. - A thought leader having 10-15 years of experience with a good balance of business acumen, domain, and technical expertise. - 5+ years building NLP/AI software professionally and successfully releasing to customers. - 5+ years of hands-on experience in building scalable systems for training & evaluating machine learning/deep learning models. - Experience in solutioning and delivering 1-2 state-of-the-art Gen AI products which include Multi-modal LLMs, Multi-modal contrastive learning, Foundation models, Diffusion-based models, and parameter-efficient fine-tuning of LLM, etc. - Experience with Cloud technologies and familiarity with Azure. - Familiarity with deploying models for large-scale inferencing & optimizations. - Solid understanding of inference speed-up techniques such as speculative decoding and optimization of LLMs for human preferences. - Strong proficiency in PyTorch, TensorFlow, Transformers, Kubernetes, Docker, LangChain, vectorDB, and cloud platforms like AWS, GCP, or Azure, and Monitoring tools like Grafana, and CI/CD tools like Airflow, GitLab, and Big Data management tools like Spark, Kafka. - Excellent presentation, written and verbal communication, engagement, and interpersonal skills along with validated skills in building great design. Thanks and Regards Sanjay Sunar US IT Recruiter | Convex Tech Inc. : [email protected] : https://www.linkedin.com/in/sanjay-sunar-918771321/ Keywords: continuous integration continuous deployment artificial intelligence machine learning information technology Gen AI Solutions Architectat Remote [email protected] |
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| Thu Aug 08 06:49:00 UTC 2024 |