Machine Learning Architect

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world’s leading Fortune 1000 organizations transform bold ideas into measurable business impact. We go beyond building innovative AI technologies—we solve the problems that matter most to our clients.

Since our founding in 2013, Quantiphihas built a proven track record of turning complex challenges into meaningful outcomes across industries.

Headquartered in Boston, with more than 4,000 professionals worldwide, we partner with global enterprises to deliver large-scale digital, cloud, and AI-driven transformation.

#Solving What Matters .

We are an Elite and Premier partner to Google Cloud, AWS, NVIDIA, Snowflake, and other leading technology platforms, and our work has been recognized across the industry, including:

• 21 Google Cloud Partner of the Year awards in the past 10 years
• 3 AWS AI/ML Partner of the Year awards
• 3 NVIDIA Partner of the Year awards
• 3 Snowflake Partner of the Year awards
• Rated Leaders by Gartner, Forrester, IDC, ISG, Everest Groupand other leading analyst firms.

Quantiphi delivers First-in-class AI solutions across Life Sciences, Healthcare, Banking, Financial Services, CPG, Manufacturing, Energy, High-Tech, Telecommunications, etc., powered by cutting-edge Generative AI and Agentic AI accelerators.

We are also proud to be certified as a Great Place to Work, reflecting our commitment to our people and our culture.

Role:
Technical Architect - Machine Learning

Employment type:
Full Time

Location:
Remote (Canada)

As an Architect, Machine Learning Engineer at Quantiphi, you will be responsible for designing and developing advanced machine learning models and algorithms to solve complex business problems. You will work on optimizing and deploying these models on AWS infrastructure, ensuring scalability and reliability.

• 8+ years of relevant hands-on technical experience implementing and developing cloud ML solutions on AWS.
• Hands on experience in AWS Machine Learning services. Proven experience using AWS Sagemaker leveraging different types of data sources, Training jobs, real-time and batch Inference, and Processing Jobs.
• Good Experience developing applications using LLMs with Langchain.
• Must have experience using GenAI frameworks such as vertex AI, OpenAI, AWS Bedrock.
• Must have Hands-on experience fine-tuning large language models (LLM) and Generative AI (GAI), specifically LLama
  2.
• Must have Hands-on experience working with (Retrieval Augmented Generation) RAG architecture and experience using vector indexing such as Open search, Elasticsearch.
• Strong familiarity with higher-level trends in LLMs and open-source platforms.
• Should have experience with Deep Learning Concepts. Transformers, BERT, Attention models
• Prompt Engineering:
  Engineerprompts and optimizefew-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations.
• Model Evaluation &Optimization:
  Evaluate LLM'szero-shot and few-shotcapabilities, fine-tuning hyperparameters, ensuring task generalization, and exploring model interpretability for robust web app integration.
• Response Quality:
  Collaborate with ML and Integration engineers to leverage LLM's pre-trained potential, delivering contextually appropriate responses in a user-friendly web app.
• Implement and manage MLOps principles and best practices for Gen AI models
• Thorough understanding of NLP techniques for text representation and modeling
• Able to effectively design software architecture as required
• Experience with at least one of the workflow orchestration tools, Airflow, Step Functions, Sage Maker Pipelines, Kubeflow etc. Knowledge of a variety of machine learning techniques (Supervised/unsupervised etc.) (clustering,…