Senior Machine Learning Operations Engineer, Dandy
Computer Vision
Helping dentists deliver better care and brighter smiles with technology
Be an early applicant
Helping dentists deliver better care and brighter smiles with technology
1001+ employees
Be an early applicant
1001+ employees
Company mission
To become the best digital dental lab for every dentist.
Role
Who you are
- 5+ years of software experience and 3+ years MLOps engineering experience, preferably in a high growth startup environment
- 1+ years of experience working directly with machine learning model training and evaluation preferred
- Hands-on experience working with ML models for performance and training optimizations, hyperparameter tuning, model monitoring, evaluation, and benchmarking
- Hands-on experience with one of the cloud platforms such as AWS, GCP or Azure. Experience with Google Cloud services (e.g., Vertex AI, BigQuery, Dataflow, Compute Engine, Kubernetes Engine) is preferred
- Familiarity with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn)
- Experience building and maintaining CI/CD pipelines with best practices
- Familiarity with containerization tools (e.g., Docker, Kubernetes) and orchestration platforms (e.g. Kubeflow)
- Comfort working in a highly agile, intensely iterative software development process
- Self-motivated, self-managing and takes ownership, with excellent organizational skills
- Ability to thrive in a remote-first organization
What the job involves
- We are hiring a Senior MLOps engineer to join our rapidly growing Machine Learning team. As a member of the Machine Learning team, you will play a key role in the success of our team and company
- You'll constantly be challenged to learn new technologies, establish best practices, and be given the freedom to solve problems on your own and learn by doing
- We are creating next-generation experiences across the newly 3D-digitized dental stack with ML models, so our ML platform is critical to our success
- As a Senior MLOps Engineer, you will be key to the development of our ML platform to create various state-of-the-art machine learning models to revolutionize the digital dental industry
- In collaboration with ML engineers, design and implement MLOps pipelines for 2D & 3D dataset curation, model training, evaluation, optimization, and deployment
- Manage and optimize cloud-based infrastructure for ML workloads, including scaling, resource allocation and cost management
- Help engineer information feedback loops to continuously improve our machine learning models
- Develop and implement automation strategies for model training, evaluation, optimization, and deployment to improve efficiencies
- Develop and manage monitoring solutions using GCP tools like Cloud Monitoring and Cloud Logging to track model performance, system health, and operational metrics
- Ensure that ML operations comply with data security and privacy regulations, utilizing security features and best practices
- Collaborate with other stakeholders within Engineering and Data to maintain a high bar for quality in a fast-paced, iterative environment
Our take
Dentistry, a $400B industry, has long relied on outdated practices. Dandy was created to modernize and simplify dental operations by integrating technology into every aspect of the dental practice. Its goal is to streamline workflows, making dental practices more efficient and easier to manage.
While other startups have tried to bring technology to the dental field, Dandy distinguishes itself by understanding the industry's complexity and respecting the way dentists operate. Rather than overwhelming practitioners with a complete overhaul, Dandy introduces new features gradually, such as digitizing dental labs for procedures like crowns and implants. It makes the dental experience seamless for both sides of the chair, and to date, more than 2 million people use a Dandy dental product daily.
Dandy aims to build a full operating system for dental practices, offering a "business-in-a-box" solution that allows dentists to focus on patient care while the platform handles administrative and operational tasks. While this vision has the potential to bring immense value to a field in need of innovation, the challenge lies in overcoming dentistry's resistance to change. Patience and persistence will be key as Dandy reshapes how dental professionals run their practices.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
12% employee growth in 12 months
Company
Funding (1 round)
Apr 2019
$4.4m
SEED
Total funding: $4.4m
Company benefits
- Comprehensive health plans: Your health is our top priority. We offer a range of comprehensive medical, dental, and vision plans so you can choose what works best for you. Some plans include employer contributions to Health Savings Accounts (HSAs), and we offer options that cover 100% of employee-only premiums.
- Flexibility, built-in: At Dandy, we flex-first, which means trusting you to own your day and deliver, working where and how you want. We believe that by embracing flexibility, we empower everyone to balance work and life in the way that works best for them. Some roles need to be on-site due to the nature of the work.
- Investing in your wellbeing: Your wellbeing is more than just physical health—that’s why our benefits are designed to support you in all aspects of life. From mental health resources included in our healthcare plans to perks like pet insurance, a gym stipend, and access to discount platforms like Perkspot, we offer a range of programs to help you feel your best—inside and outside of work.
- Shared Success: We believe in shared success—when the business wins, our employees do too. Through performance-based bonuses and equity opportunities, our team shares in the impact we create together.
Company HQ
Tribeca, New York, NY
Leadership
Toni Oloko
(Co-Founder)Previously worked in Special Projects at goPuff. Before that founded PracticeGigs which they went on to sell.
Daniel Hanover
(Co-Founder)Previously worked as a Product Manager at Yelp and as a Software Engineer at Facebook. Studied Management and Technology at Wharton.
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