Machine Learning Architect

Quantiphi; Boston (MA); Hybrid; CAD 150,000 - 190,000; Full time

Job summary

Quantiphi, an award-winning AI-first digital engineering company, seeks a Technical Architect - Machine Learning for remote Canada-based work. You will design and deploy advanced ML models on AWS, optimize inference pipelines, and ensure scalable, reliable cloud solutions.

You will leverage LLMs, GenAI frameworks, and RAG architectures, collaborating with cross-functional teams to deliver production-ready AI capabilities for Fortune 1000 clients.

Qualifications

• 8+ years of hands-on experience building cloud ML solutions on AWS.
• Experience with AWS SageMaker and real-time/batch inference.
• Experience with LLMs and LangChain.
• Experience with GenAI frameworks (Vertex AI, OpenAI, AWS Bedrock).
• Fine-tuning LLMs (LLama2) and RAG architecture.
• Vector indexing with OpenSearch/Elasticsearch.
• Knowledge of Transformers, BERT, attention mechanisms.
• Prompt engineering and few-shot techniques.

Responsibilities

• Design and develop advanced ML models and algorithms.
• Optimize and deploy models on AWS infrastructure.
• Ensure scalability and reliability of deployments.
• Collaborate with ML and integration engineers on web app integration.

Skills

AWS

SageMaker

LangChain

GenAI frameworks

RAG architecture

OpenSearch/Elasticsearch

NLP techniques

MLOps

Tools

LangChain

Vertex AI

OpenAI

AWS Bedrock

OpenSearch

Elasticsearch

Job description

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 partnerwith global enterprises to deliver large-scale digital, cloud, and AI-driven transformation.

#SolvingWhatMatters.

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)

What You Will Do:

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.

Basic Qualifications:

• 8+ years of relevant hands-on technical experience implementing and developing cloud ML solutions on AWS.
• Hands on experience in AWS MachineLearning services. Provenexperience using AWS Sagemaker leveraging different types of data sources, Trainingjobs, 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 LLama2.
• Must have Hands-onexperience working with (Retrieval Augmented Generation) RAG architecture and experience using vector indexing such as Opensearch, Elasticsearch.
• Strong familiarity with higher-level trends in LLMs and open-source platforms.
• Should have experience with Deep LearningConcepts. 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, StepFunctions, SageMaker Pipelines, Kubeflow etc. Knowledge of a variety of machine learning techniques (Supervised/unsupervised etc.) (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
• Ability to create end to end solution architecture for model training, deployment and retraining using native AWS services such as Sagemaker, Lambda functions, etc.
• Ability to collaborate with cross-functional teams such as Developers, QA, Project Managers, and other stakeholders to understand their requirements and implement solutions.

Good to have skills:

• Experience of working for customers/workloads in the Edtechdomain with use cases.
• Experience with software development

What is in it for you:

• Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact on scale.
• Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
• Work with Fortune500 companies and disruptive innovators in a research-driven environment with 60+ patents.
• Stay ahead of the curveby gaining hands-onexperience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling