Machine Learning Engineer (Hybrid) Austin, TX

Machine Learning Engineer (Hybrid - Onsite 2 days a week)

The Machine Learning Engineer at Weedmaps will be a key technical contributor within our Data organization. In this role you will build and deploy sophisticated AI and machine learning systems that power our marketplace and e-commerce platform. The ideal candidate is a hands-on ML practitioner with strong software engineering fundamentals who can build end-to-end systems that deliver measurable business impact. You will collaborate extensively with cross-functional teams, including Product to understand user needs and translate them into ML solutions; Engineering to integrate ML systems into our broader ecosystem; Data and Analytics to leverage insights and coordinate on data strategies; as well as stakeholders across the business to ensure ML initiatives are aligned with company objectives.

As part of our Data organization, you will develop and deploy machine learning solutions that address unique challenges in our marketplace, including product matching, personalized recommendations that comply with complex regulatory requirements, and data-driven optimizations across our marketplace. The explosive growth of the cannabis industry requires increasingly sophisticated ML solutions that can scale with our business.

The impact you'll make

Develop production-ready Python-based ML models with a focus on advanced NLP, similarity metrics, and product matching and recommendations

Create and refine machine learning pipelines that can handle the unique challenges of our product data, including inconsistent naming and categorization

Develop comprehensive evaluation frameworks including evals and metrics to benchmark ML model performance in real-world scenarios

Implement automated evaluation pipelines to continuously monitor model performance in production

Build and maintain scalable ML infrastructure using a mix of managed services (eg AWS SageMaker) and custom services (such as function as a service apps on Kubernetes)

Implement best practices for model serving, versioning, and monitoring in production environments

Optimize model deployment pipelines for reliability, performance, and cost-efficiency

Design, implement, and analyze A/B (or MAB) tests to evaluate ML system performance in production systems (e.g. with Optimizely or similar tools), ensuring that ML systems achieve business objectives

Design and build API-based microservices that integrate ML functionality into our broader engineering ecosystem, ideally creating reusable ML components that can be leveraged across multiple product lines

What you've accomplished

Bachelor's degree in Computer Science, Data Science, or related quantitative field

2+ years of experience building and deploying machine learning models in production environments

4+ years of relevant experience in Machine Learning, Data Science, Data/Software Engineering

Strong programming skills in Python and experience with modern LLM endpoints

Experience with MLOps practices for model monitoring, maintenance, and lifecycle management

Demonstrated expertise in machine learning algorithms and frameworks (e.g. TensorFlow, PyTorch, or scikit-learn) as well as modern LLM systems (Anthropic, OpenAI) with a proven track record of deploying models to production

Proficiency in software engineering best practices, including version control, code review, testing, and documentation

Strong understanding of data engineering principles and experience with data preprocessing, feature engineering, and data quality assurance

History of effective collaboration with cross-functional teams to deliver ML solutions that drive measurable business results

Experience communicating complex ML concepts to both technical and non-technical stakeholders

Experience with cloud computing platforms, preferably AWS (particularly SageMaker and Bedrock)

Experience using AI endpoints such as Claude or ChatGPT for embeddings and more advanced AI pipeline use cases such as hybrid ranking systems leveraging RAG with AI-based re-rankers that optimize specific metrics (e.g. precision)

Successfully built and deployed ML systems that solved real business problems in e-commerce or marketplace environments

E-commerce or marketplace business experience preferred

Regulated industry experience - nice to have

The base pay range for this position is $181,875.00 - $200,645.00 per year

Benefits

2025 Benefits for Full Time, Regular Employees include: employee-employer paid premium 100%, company contribution to a HSA when electing the High Deductible Health Plan

For plans that offer coverage to dependents, you pay a small contribution

Free access to CALM app for employees and dependents

Employee Training

Mental Health seminars and Q&A sessions

Basic Life & AD&D - employer paid 1x salary up to $250,000

401(k) Retirement Plan with employer match contribution

Generous PTO, Paid Sick Leave, and Company Holidays

Supplemental, voluntary benefits

Student Loan Repayment/529 Education Savings - including a company contribution

FSA (Medical, Dependent, Transit and Parking)

Voluntary Life and AD&D Insurance

Critical Illness Insurance

Short- and Long-term Disability Insurance

Pet Insurance

Family planning/fertility

Identity theft protection

Legal access to a network of attorneys

Paid parental leave

Generous PTO and company holidays

Why Work at Weedmaps?

You get to work at the leading technology company in the cannabis industry

You get to play a meaningful role in helping to advance cannabis causes, including helping improve the lives of patients who rely on the benefits of cannabis

You get an opportunity to shape the future of the cannabis industry

You get to work on challenging issues in a collaborative environment that encourages you to do your best

You get to work in a casual and fun environment; no fancy clothes required, but you are free to dress to the nines!

Numerous opportunities and tools to learn and grow your professional skills

Endless opportunities to network and connect with other Weedmappers through speaker series, Employee Resource Groups, happy hours, team celebrations, game nights, and much more!

Weedmaps is an equal opportunity employer and makes employment decisions on the basis of merit. The Company prohibits unlawful discrimination based on race, religion, color, national origin, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, military status, veteran status, or any other characteristic protected by law. 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.

Applicants are entitled to reasonable accommodations under the Americans with Disabilities Act and applicable state/local laws, unless the accommodation presents undue hardship. Please email peopleoperations at weedmaps.com if you would like to confidentially discuss a potential accommodation during the interview process.

About Weedmaps

WM Technology, Inc.’s (Nasdaq: MAPS) mission is to power a transparent and inclusive global cannabis economy. Now in its second decade, WM Technology has been a driving force behind legislative change in the cannabis space. Founded in 2008, WM Technology provides B2C and B2B software solutions. The cloud-based SaaS solutions from WM Business provide an end-to-end operating system for cannabis retailers. WM Business’ tools help ensure compliance with evolving regulations. Through its website and mobile apps, WM Technology provides consumers with information about cannabis retailers, brands, and products, facilitating product discovery and engagement with our customers. WM Technology supports remote work for all eligible employees. Visit us at www.weedmaps.com.

Notice to prospective Weedmaps job applicants

Our recruiters will communicate with candidates through an @weedmaps.com email address.

CORRECT: [email protected]

INCORRECT: [email protected]

Our recruiters will NEVER ask for or solicit payment from applicants to apply, interview, or work for Weedmaps.

If you are interested in a role at Weedmaps, please apply through our established channels.

If you are unsure if a communication is legitimate, please contact our recruitment team at [email protected] for verification.

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