ML Ops Engineer

Sorry, this job was removed at 12:26 p.m. (CST) on Friday, Nov 22, 2024
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San Jose, CA
186K-220K Annually
Internship
Artificial Intelligence • eCommerce
The Role

Coactive makes it easy to search, filter, and analyze visual content. Increasingly image and video data captures the content we watch, the products we buy, and the work we do, and already represents 80% of internet traffic. But rather than being an asset, visual content is often a tax or even a liability because it is so hard to work with and understand. Coactive solves this by bringing structure to unstructured visual data. Rather than spending months (or years) building complex infrastructure, data teams can unlock the value of their visual data in minutes to power use cases such as content understanding and moderation, search, and analytics.

Coactive was founded by experts who shaped the fields of high-performance deep learning and data-centric AI. We have the scars from building and working with the first generation of modern machine learning systems at Google, Meta, Pinterest, eBay, Lyft, and other leading organizations. Through our decades of experience, we have developed a playbook to democratize the toughest parts of machine learning systems; no PhD required.

This is an exceptional opportunity to work with one of Forbes' top 50 AI companies, backed by key investors such as Andreesen Horowitz and Bessemer Ventures. This position is truly a chance to be part of a category-defining team that is attracting top-tier talent interested in pushing the boundaries of what's possible in AI. 

As an ML Ops Engineer at CoactiveAI, you will play a crucial role in designing, building, and maintaining our ML infrastructure. You will work closely with research scientists, ML Engineers, software engineers, and product managers to deploy and monitor machine learning models in production. Your expertise will ensure the robustness, scalability, and reliability of our AI solutions.


What you’ll do:

  • Design and implement scalable and reliable ML pipelines.
  • Automate the deployment and monitoring of ML models.
  • Collaborate with ML Engineers, Applied ML Researchers and software engineers to integrate ML models into applications.
  • Optimize model performance and scalability.
  • Enable Research scientists with experimentation, validation and productionisation of new models.
  • Monitor and troubleshoot production ML systems to ensure high availability and reliability.
  • Implement and enforce best practices for ML Ops, including versioning, testing, and validation.


What we're looking for:

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  • 5+ years of experience in ML Ops, DevOps, or related roles.
  • Strong programming skills in Python.
  • Proficiency with ML frameworks such as MLFlow, TensorFlow, PyTorch, or scikit-learn.
  • Hands-on experience using big data technologies such as Spark and Kafka.
  • Experience with cloud platforms such as AWS, Google Cloud, or Azure.
  • Solid understanding of containerization and orchestration technologies like Docker and Kubernetes.
  • Experience with data engineering and ETL processes.
  • Experience of database systems, both SQL and NoSQL.
  • Familiarity with CI/CD tools such as Github Actions, Jenkins, GitLab CI, or CircleCI.
  • Experience with monitoring tools like Datadog, NewRelic, or similar.
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and collaboration abilities.


Preferred Qualifications:

Experience with model interpretability and explainability tools.

What you can expect from us:

This is a hybrid position based in San Jose, California.

The estimated annual base salary for this position is between *$186,000-$220,000.

At Coactive, cash salary is only one part of our total compensation package. Other benefits for this position include, but are not limited to:

  • Equity grants
  • 100% medical, dental, & vision coverage for you
  • Medical, dental, & vision partially covered for your dependents
  • Unlimited PTO
  • Social events ranging from book clubs, happy hours, and hiking to board game nights and games of Mario Kart.

Further, you can expect a supportive work environment from us. We build products, but we develop people. 

Join us in revolutionizing how businesses harness the power of machine learning to unlock the potential of unstructured data. If you're passionate about driving innovation and delivering unparalleled customer experiences, we'd love to have you on board.


*Actual pay is dependent on an individual candidate’s professional background, experience, skills and qualifications, as well as market demand and business demands. This pay range is subject to change and may be modified in the future. The salary, other compensation, and benefits information is accurate as of the date of this posting.

We embrace and celebrate the diversity of our employees. We are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, veteran status, or other class protected by applicable law. We are proud to be an equal opportunity workplace.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

The Company
HQ: San Jose, CA
15 Employees
On-site Workplace

What We Do

At Coactive AI, we are empowering data practitioners and data-driven teams to unlock insights in unstructured image and video data. This visual data increasingly captures everyday life from our online experiences on e-commerce sites and social media to guiding the cars we drive and monitoring the plants we eat. By 2021, unstructured visual data will be more than 82% of all internet traffic. We make this unstructured visual data useful by bringing it into the world of SQL and the big data tools that teams already love.

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