This is an applied machine learning position with a strong emphasis on engineering, not research. You will play a key role in advancing our ML Ops and ML Engineering capabilities.

What you'll be doing:

• Drive projects from ideation to production, including feature engineering, model selection, deployment, and model observability and evaluation.
• Gather product requirements and translate them into robust ML system design requirements.
• Work on a variety of information extraction, information storage and information retrieval problems from both structured and unstructured data sources.
• Architect efficient and scalable systems to support serving inference services.
• Develop reusable AI-based services — including ML models, foundation models, and agents — that will be consumed by other backend services at Affinity.
• Lead complex technical initiatives and provide technical guidance for peers through system design reviews, code reviews and promoting best practices.
• Collaborate with cross-functional teams (product, infra, data engineer, and software engineer) and ML engineering teams to build robust, high-scale systems that underlie all of our data processing and ML Operations.

Qualifications Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you're excited about this role, but your past experience doesn't perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Required:

• 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production, with a focus on ML Engineering and ML Ops.
• Experience in the following technical areas:

• Architecture design for distributed systems
• Building maintainable and testable codebases and services
• Developing ML systems, such as recommendation systems and information retrieval solutions.
• Relational DB, non-relational DB, and vectorDB.
• Developing AI applications powered by LLMs and/or agents.
• Proficient in building services in Python and familiar with common ML frameworks, such as PyTorch and Scikit-learn.

• Experience with observability tools for both online and offline evaluation and tracing for AI applications.
• Demonstrated experience working with large datasets, and are comfortable with high-scale data ingestion, transformation, analysis, and prediction tools.
• Experience working collaboratively with engineering, product, data, and other cross-functional teams.

Nice to Have:

• Experience with developing machine learning applications at scale, from inception to driving user impact.
• Familiar with serving machine learning models for streaming and batch inference at scale.
• Experience with packaging, CI/CD and pipeline automation.
• Good understanding of machine learning systems' testing, benchmarking, and online monitoring.
• Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvement.

Tech stack : Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference. We maintain the Docker images and deployment pipeline via CircleCI. Our data stack includes Spark, Python, Kafka, and Databricks.

How we work: Our culture is a key part of how we operate, as well as our hiring process:

• We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
• We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with.
• We make data-driven decisions and make the best decision for the moment based on the information available.

If you'd want to learn more about our values click here.

What you'll enjoy at Affinity:

• We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.
• Health Benefits: We cover both you and your dependents' extended health benefit premiums and offer flexible personal & sick days to support your well-being.
• Retirement Planning: We offer an RRSP plan to help you plan for your future.
• Learning & Development: We provide an annual education budget and a comprehensive L&D program.
• Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
• Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.

Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job.

A reasonable estimate of the current range is $113,000 to $187,000 CAD . Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant.

About Affinity With more than 3,000 customers worldwide and backed by some of Silicon Valley's best firms, Affinity has raised $120M to empower dealmakers to find, manage, and close more deals. How? Our Relationship Intelligence platform uses the wealth of data exhaust from trillions of interactions between Investment Bankers, Venture Capitalists, Consultants, and other strategic dealmakers to deliver automated relationship insights that drive over 450,000 deals every month. We are are proud to have received Inc. and Fortune Best Workplaces awards as well as to be Great Places to Work certified for the last 5 years running. Join us on our mission to make it possible for anyone to cultivate and fully harness their network to succeed.

We use E-Verify Our company uses E-Verify to confirm the employment eligibility of all newly hired employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.dhs.gov/E-Verify.