Architect - Machine Learning

Quantiphi; Boston (MA); Hybrid; CAD 130,000 - 190,000; Full time

Benefits offered by this job

Remote Canada

Competitive salary

Health benefits

Job summary

Quantiphi, an AI-first digital engineering company, seeks an Architect, Machine Learning Engineer to design and deploy advanced ML models on AWS, ensuring scalability and reliability for enterprise clients.

You will work remotely from Canada, collaborate with cross-functional teams, and leverage GenAI, LLMs, and NLP techniques to deliver production-ready solutions.

Qualifications

• 8+ years of hands-on ML/AI engineering experience.
• Experience implementing cloud ML solutions on AWS.
• Proficient with LangChain and GenAI frameworks.
• Hands-on with LLMs and vectors/indexing.
• Familiarity with NLP techniques and model evaluation.

Responsibilities

• Design and develop advanced ML models and algorithms.
• Deploy and optimize models on AWS infrastructure for scalability and reliability.
• Collaborate with cross-functional teams to ship production-grade AI solutions.
• Explore and implement retrieval augmented generation (RAG) architectures and vector stores.

Skills

AWS ML services

LangChain

GenAI frameworks

LLMs

RAG

NLP techniques

Prompt engineering

Deep learning

Tools

AWS SageMaker

Langchain

OpenAI

Vertex AI

Elasticsearch

Opensearch

Airflow

Kubeflow

SageMaker Pipelines

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, Quantiphi has 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. #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 Group and 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.

Experience Level: 8+ years

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 (BQ):

• 8+ years of relevant hands-on technical experience implementing, and developing cloud ML solutions on AWS.
• Hands-on experience on 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 vertexAI, OpenAI, AWS Bedrock.
• Must have Hands-on experience fine-tuning large language models( LLM) and Generative AI (GAI), specifically LLama2.
• Must have Hands-on experience 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 Learning Concepts. Transformers, BERT, Attention models
• Prompt Engineering: Engineer prompts and optimize few-shot techniques to enhance LLM's performance on specific tasks, e.g. personalized recommendations.
• Model Evaluation & Optimization: Evaluate LLM's zero-shot and few-shot capabilities, 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.

What is in it for you:

• Join one of the world’s fastest-growing AI-first digital engineering companies and make a real impact at scale.
• Lead and collaborate with a high-energy team of talented, driven individuals solving complex, meaningful challenges.
• Work with Fortune 500 companies and disruptive innovators in a research-driven environment with 60+ patents.
• Stay ahead of the curve by gaining hands-on experience with cutting-edge AI, ML, data, and cloud technologies while continuously upskilling.