Machine Learning Operations Engineer

4 weeks ago

Pittsburgh, United States Lovelace AI Full time
About Us:

Lovelace AI was born from the desire to apply state of the art AI and systems engineering to the question of human safety, especially in dangerous conditions such as conflict, disaster response, anti-terrorism and deterrence against AIs designed by adversaries to harm civilians.

How many lives can be saved by taming the information overload, confusion and conflicting priorities experienced by the people responsible for dealing with dangerous situations around the world? We believe the answer is potentially dramatic, and we are determined to create a team with the wisdom, skills, brainpower, thoughtfulness and experience to make this vision real.

Job Summary:
  • As an MLOps Engineer at Lovelace AI, you will play a key role in bridging the gap between machine learning development and operational deployment. Your primary responsibilities will include designing, implementing, and optimizing end-to-end machine learning pipelines, ensuring seamless integration with existing systems.
Key Responsibilities:
  • Deployment and Integration: Deploy machine learning models into production environments. Integrate machine learning algorithms with existing systems and applications.
  • Infrastructure Management: Design, build, and maintain the infrastructure for machine learning operations. Collaborate with DevOps teams to ensure scalability, reliability, and security of ML systems.
  • Automation: Implement automation tools and processes for model training, testing, and deployment. Streamline and optimize the end-to-end machine learning lifecycle.
  • Monitoring and Troubleshooting: Set up monitoring systems to track the performance of deployed models. Troubleshoot issues related to data pipelines, model inference, and system performance.
  • Collaboration: Work closely with data scientists, software engineers, and other stakeholders to understand model requirements and ensure smooth integration. Collaborate with cross-functional teams to align machine learning workflows with business goals.
  • Version Control: Implement version control for machine learning models and pipelines.
  • Security and Compliance: Ensure the security and compliance of machine learning systems. Implement best practices for data privacy and protection.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
  • Proven experience in deploying and managing machine learning models in production.
  • Strong programming skills in one or more languages such as Python, Go, C, C++, Bash.
  • Knowledge of cloud platforms (AWS, Azure, GCP) and their machine learning services.
  • Familiarity with DevOps practices and tools.
  • Understanding of continuous integration/continuous deployment (CI/CD) pipelines.
  • Excellent problem-solving and communication skills.
  • Must be a US Citizen.
Preferred Skills:
  • Knowledge of machine learning frameworks (TensorFlow, PyTorch, JAX, XLA).
  • Experience with orchestration tools (Airflow, Kubeflow).
  • Familiarity with MLOps tools and platforms.
  • Strong understanding of data engineering concepts.
  • An ability to deploy and manage build systems that integrate a variety of languages and platforms, e.g., Bazel.
  • Experience with containerization technologies (e.g., Docker, Kubernetes).
  • Experience developing custom with machine learning benchmarking systems on platforms such as TensorBoard, Weights & Biases, neptune.ai, etc.
  • Familiarity with machine learning deployment tools such as TFLite, ONNX, TensorRT, and ML Kit.


Benefits:

LovelaceAI offers competitive compensation packages, comprehensive benefits. We provide a supportive and inclusive work environment where your skills and expertise can make a significant impact on the safety and security of our communities.

Lovelace's founding team includes:

Andrew Moore, who has a track record of building impactful AI systems, designing them with human rights impact assessments as a top priority, leading the AI division of one of the world's foremost cloud companies, and actively participating in machine learning and AI research over the past two decades.

Brendan Dunne, a career Special Operations veteran and retired Army officer who has led high performing cross functional teams the past 20 years in the country's premier national mission force. He was most recently in charge of US Special Operations Command's Global Analytics Platform (aka the GAP), one of DoD's leading technology platforms.

Toby Smith, well known in the Pittsburgh Tech community for his engineering leadership and design skills, and who has led many of the most ambitious and complex system infrastructure projects in Google Pittsburgh and NetApp.

Here is a note from Andrew Moore to people who are reading these Job Postings:

"Hi folks, I'm so glad you are potentially interested in Lovelace AI. This area means a lot to me because while I am an AI optimist, I also think that we technologists owe it to a rightly skeptical world to show that modern intelligent systems can actually be useful. Usefulness comes in many guises: from life sciences to education and from transportation to entertainment and many others. For many of us, security and public safety is also very high on that list. That reasoning leads to this conclusion: I'm determined to make sure that the people building Lovelace AI gain a lot from the experience, including the chance to solve fascinating problems in computer science, AI, business development, customer success and product management. I also hope that we all learn from each other in a highly enriching work environment. But my main hope is that we have a shared sense of accomplishment as we see an increasing number of national security and public safety domains made safer through sensible and robust use of advanced computer science."

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