Wizard is looking for a Staff Machine Learning Engineer to develop dialog systems. Responsibilities include building training pipelines for LLMs, deploying models, and addressing customer issues. A strong background in ML and Python is preferred.
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 $235,000 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 • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
As a Senior Staff Machine Learning Engineer, you will design and implement infrastructure and features for AI workloads, improve SRE practices, and mentor colleagues.
Top Skills:
AnsibleGitlab CiGoHelmInfrastructure As CodeJ2EeJavaKubernetesLinuxNvidia GpusPrometheusPythonSoftware-Defined NetworkingSplunk
Artificial Intelligence • Blockchain • Fintech • Financial Services • Cryptocurrency • NFT • Web3
The Staff Machine Learning Engineer will design and implement ML models for document processing, risk assessment, and develop real-time ML pipelines while collaborating with platform teams to deploy scalable models.
Top Skills:
Automated Document ProcessingDeep Neural NetworksDistributed SystemsGenerative AiLarge Language ModelsMachine LearningRisk AssessmentTransformers
Artificial Intelligence • Big Data • Healthtech • Machine Learning • Analytics • Biotech
Design and build data infrastructure for multimodal ML models in healthcare, optimizing large-scale data workflows and ensuring model training efficiency.
Top Skills:
SparkDaskHugging Face DatasetsKubeflowMlflowMosaicml StreamingPythonRaySagemaker
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
