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Lead Machine Learning Ops Engineer
Location : Hadapsar, Pune, Maharashtra
Headquarters : Ireland
Hiring Mode : Full Time
Hiring Role : DevOps Engineer
Experience : Mid Level
- Demonstrate exceptional impact in delivering projects, products and/or platforms in terms of scalable data processing and application architectures, technical deliverables and delivery throughout the project lifecycle.
- Responsible for ensuring that ML deployment pipelines can maintain and monitor model accuracy and ensure application code quality.
- Work on developing the Intelligence layer MLOps pipelines, ensuring that infrastructure and code is delivered incrementally and according to our internal security deployment policies.
- Responsible for ensuring model development is deployable and sustainable at scale and meets the business needs.
- Author high-quality, high-performance, unit-tested code to extract and transform data based on business and data science needs
- Must be conversant with Agile methodologies and tools and have a track record of delivering products in a production environment.
- Work directly with stakeholders, engineering, and test to create high quality solutions that solve end-user problems.
- Develop and execute agile work plans for iterative and incremental project delivery
- Explore and recommend new tools and processes which can be leveraged across the data preparation pipeline for capabilities and efficiencies.
- Ensure that our development and deployment are tightly integrated to each other to maximize the deployment user experience.
- Curator for all code and binary artifact repositories (containers, compiled code)
- Requires a minimum of a Bachelor level degree in computer science or equivalent software engineering discipline.
- 7+ years of experience in a relvant and comparable role in the software industry, with a proven track record of success.
- Proficient in Python and Linux environments to support model training, analysis and prediction pipelines for our advanced analytics services.
- Experienced in designing and building highly distributed and scalable Analytics/Data Science/Machine Learning pipeplines hosted in major public and/or private cloud providers such as Azure, AWS or Google Cloud.
- Proficient in developing and maintaining AI & ML DevSecOps pipelines to support Model training and prediction requirements.
- Experience with Docker & Docker orchestration technologies (e.g. Kubernetes (K8S), Docker compose).
- Ability to develop Machine learning and validation pipelines in a secure and enterprise grade environment.
- Strong problem solving and software debugging skills with a track record of delivery and a willingness to roll up sleeves to get the job done.
- Excellent verbal and written communication skills including the ability to effectively explain technical concepts.
- Masters or equivalent degree in computer science or comparable software engineering discipline.
- Experience in deployment of Infrastructure-as-Code using Terraform.
- Proficiency with cloud technologies (IaaS, PaaS, serverless technology) micro-service design, CI/CD and DevOps technologies.
- Experience in Knowledge Graphs and integration this technology into intelligence pipelines.
- Experience in building and deploying AI/ML models in large scale production projects with modern light-weight design (API, Microservices etc.)
- Experience with ML frameworks and libraries such as TensorFlow, Keras, Pytorch and Kubeflow.
- Experienced in big data orchestration frameworks such as Apache Airflow.
- Knowledgeable in leveraging data transit protocols and technologies (AMQP, MQTT, Rest API, JDBC, etc).
- Knowledge of multiple cloud and edge technologies, especially Microsoft Azure e.g. Databricks, Azure IoT Edge.
- Knowledge of cloud development platforms such as Azure or AWS and their associated data storage options.
- Experience in integrating Artifact repositries (eg JFrog Artifactory) into CI/CD pipeline to manage and control access to binary dependancies
- Experience with Agile development methodologies and concepts.
- Keeps abreast of upcoming software development/engineering tools, trends, and methodologies.
- Good judgment, time management, and decision-making skills.