Overview:
We are seeking a Machine Learning DevOps Developer that will play a critical role in architecting & developing cloud solutions that employ the latest machine learning and AI technologies.
Successful candidates will have excellent analysis, communication, and collaboration skills.
Description:
Build, test and maintain the infrastructure and tools to facilitate the consistent and automated AI software solution development and release process.
Design, build and maintain the ML CI/CD pipeline that automates data collection, data analysis, experimentation, model training, model serving and monitoring in production.
Achieve continuous delivery of AI software solution and updates to production at scale.
Provide direction to more junior engineers.
Collaborate with data scientists, engineers, product teams and other key stakeholders.
Actively seek ways to improve software development and operation process.
Minimum Education and/or Qualifications:
Bachelor’s degree in Computer Science or a related field with 7 years of experience.
Or Master’s degree in Computer Science or a related field with 5 years of experience.
5-7 years of relevant experience in roles involving machine learning, software development, DevOps, or a combination thereof.
Experience in progressively challenging roles with demonstrated leadership, project management, and the ability to architect and implement complex systems.
Deep understanding of machine learning concepts, algorithms, and workflows.
Familiarity with various types of machine learning models (e.
g.
, supervised learning, unsupervised learning, reinforcement learning).
Experience with real-world machine learning applications and challenges, including data preprocessing, feature engineering, model selection, and evaluation.
Knowledge of industry-specific requirements and compliance standards (e.
g.
, GDPR, HIPAA, HITRUST) a plus.
Preferred Skills:
Strong DevOps, Data Engineering and ML background.
Familiar with best practices in the data engineering and MLOps community.
Experience building and maintaining CI/CD pipelines.
Demonstrated experience on a broad range of DevOps tools such as Ansible, Docker, Kubernetes, Jenkins etc.
Experience building, deploying and maintaining ML models in production.
Experience with MLOps tools such as ModelDB, MLFlow and Kubeflow.
Familiarity with python tools for data science.
Experience with cloud infrastructure.
Experience with Google Cloud Platform a plus.
Excellent communication and teamwork skills.
Ability to collaborate effectively with internal business stakeholders, outside partners and technology teams.
Proficiency in programming languages such as Python, R, or Scala.
In-depth knowledge of machine learning frameworks and libraries (e.
g.
, TensorFlow, PyTorch, scikit-learn).
Strong understanding of DevOps principles and practices.
Knowledge of infrastructure as code (IaC) tools like Ansible, Terraform, or CloudFormation.
Experience with monitoring and logging tools such as Prometheus, Grafana, ELK stack (Elasticsearch, Logstash, Kibana), or similar.
Understanding of networking, security, and data management principles.
Ability to work with big data technologies (e.
g.
, Hadoop, Spark, Kafka).
Strong problem-solving and troubleshooting skills.
Additional Notes:
Fully Remote Position
Must be W2