Develop and maintain ML systems, deploy models, fine-tune LLMs, and handle customer issues while integrating latest AI advancements.
About Us
Wizard is revolutionizing the shopping experience using the power of generative AI and rich messaging technologies to build a personalized shopping assistant for every consumer. We scour the entire internet of products and ratings across brands and retailers to find the best products for every consumer’s personalized needs. Using an effortless text-based interface, Wizard AI is always just a text away. The future of shopping is here. Shop smarter with Wizard.
The Role
Wizard is hiring ML Engineers, preferably with a background in NLP, to work on all aspects of dialog systems, from fine-tuning LLMs to serving models and building data pipelines and entity resolutions. If you don’t have an NLP background but have deep experience with Python and some exposure to ML and you are excited about the space and willing to learn, we would still encourage you to apply.
Key Responsibilities:
- Build and maintain a training pipeline for fine-tuning open-source LLMs. Testing different LLM architectures at different sizes and quantizations is important.
- Serve and Deploy the LLM on GPUs. It is important to know different configurations ahead of time to ensure we don’t OOM at runtime.
- Formulate novel product issues to ML problems and propose and iterate on solutions quickly. We value the fast pace of development.
- Triage customer issues to model/system shortcomings and communicate the complex architecture in a simple, comprehensible way to internal stakeholders.
- Keep up with the fast-growing generative AI space and incorporate the latest developments into our system.
You
- MS/Ph.D. in computer science, mathematics, or another quantitative discipline or exceptional work experience in ML engineering.
- 5+ years ML Experience.
- Experience developing machine learning-driven products at scale.
- Experience solving problems using Machine Learning with PyTorch.
- Exceptional understanding of designing ML systems in production at scale and applying a quantitative approach to identifying performance bottlenecks and cost/performance tradeoffs.
- Practical experience with large data systems, data models, and batch and streaming data pipelines.
- Ability to ramp up quickly on our tech stack, which includes GCP, Kubernetes, Airflow, Pandas, PyTorch, Python, and Node.js.
- Extensive experience with model deployment, both static within applications and dynamic, using Flask, FastAPI, or similar frameworks.
The expected salary for this role is $210,000 - $260,000 depending on skills and experiences.
Benefits
- Early-stage startup with massive growth potential and ability to grow as Wizard grows
- Competitive compensation packages, including equity
- Health
- Comprehensive, high-quality medical coverage
- Dental & vision insurance
- OneMedical memberships for you and dependents
- Spring health platform for mental healthcare personalized to your needs
- XP Health eyewear benefits ($180, 3x per year)
- Rightway Health Guide
- Wealth
- 401(k) Plan
- Life & Disability insurance covered by Wizard
- Work/Life
- Flexible PTO and sick time to take care of yourself and your family
- 12 paid holidays
- 16 weeks parental leave for primary and secondary caregivers
Top Skills
Airflow
Fastapi
Flask
GCP
Kubernetes
Node.js
Pandas
Python
PyTorch
Similar Jobs
Artificial Intelligence • Healthtech • Machine Learning • Software • Biotech
As a Machine Learning Engineer III, you will design and optimize ML infrastructure, develop scalable ML workflows, and collaborate with various teams to integrate innovative ML methods into production systems.
Top Skills:
AirflowArgoAWSDockerGithub ActionsGitlabHelmKafkaKubeflowKubernetesNumpyPandasPythonPyTorchRayScipyTensorFlowTerraform
Healthtech • HR Tech
The Sr. Machine Learning Engineer will train and evaluate models, write production code, create data systems, and collaborate with teams on ML solutions.
Top Skills:
KubernetesPython
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Machine Learning Engineer will develop scalable ML systems, create APIs, and write production-quality code while collaborating with cross-functional teams to deliver business solutions.
Top Skills:
AgileAWSCi/CdGitGCPOraclePythonSnowflakeSQL
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
