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Specialist Software Engineer - Full Stack AI / ML/GenAI

  • Source: Naukri
  • Amgen Inc
  • On-site
  • Hyderabad
  • Full-Time
  • Senior

Job Description

Role Description:

The Software Engineer is responsible for designing, developing, and maintaining software applications and solutions that meet business needs and ensuring the availability and performance of critical systems and applications. This role involves working closely with product managers, designers, and other engineers to create high-quality, scalable software solutions and automating operations, monitoring system health, and responding to incidents to minimize downtime.

Roles Responsibilities:

  • Take ownership of complex software projects from conception to deployment
  • Manage software delivery scope, risk, and timeline
  • Quickly translate concepts into working code by strong rapid prototyping skills
  • Provide technical guidance and mentorship to junior developers
  • Contribute to both front-end and back-end development using cloud technology
  • Develop innovative solution using generative AI technologies
  • Conduct code reviews to ensure code quality and adherence to best practices
  • Create and maintain documentation on software architecture, design, deployment, disaster recovery, and operations
  • Stay updated with the latest trends and advancements
  • Develop and execute unit tests, integration tests, and other testing strategies to ensure the quality of the software
  • Identify and resolve software bugs and performance issues
  • Work closely with cross-functional teams, including product management, design, and QA, to deliver high-quality software on time
  • Integrate systems and platforms to ensure seamless data flow and functionality
  • Collaborate with data scientists to develop, train, and evaluate machine learning models.
  • Build and maintain MLOps pipelines leveraging cloud platform, including data ingestion, feature engineering, model training, deployment, and monitoring.
  • Deploy machine learning models into production environments, ensuring that they are scalable and maintainable
  • Design and implement systems and processes to improve the reliability, scalability, and performance of applications
  • Automate routine operational tasks, such as deployments, monitoring, and incident response, to improve efficiency and reduce human error
  • Develop and maintain monitoring tools and dashboards to track system health, performance, and availability

Basic Qualifications and Experience:

  • Masters degree with 6 - 8 years of experience in Computer Science, IT or related field OR
  • Bachelors degree with 8 - 12 years of experience in Computer Science, IT or related field

Functional Skills:

Must-Have Skills:

  • Solid foundation in modern software design and engineering practices, with a specific focus incorporating AI and ML into solutions, including low code, microservice, serverless cloud, and containerization platforms.
  • Strong experience on Agile software development teams.
  • Strong proficiency in machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch) and MLOps (e.g., MLflow, Kubeflow, Airflow.)
  • Hands on experience with Full Stack software development. Proficient in programming language Python (preferred), JavaScript, SQL/NoSQL.

Good-to-Have Skills:

  • Strong understanding of cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes)
  • Experience with monitoring and logging tools (e.g., Prometheus, Grafana, Splunk)
  • Experience with data processing tools like Hadoop, Spark, or similar

Soft Skills:

  • Excellent analytical and troubleshooting skills
  • Strong verbal and written communication skills
  • Ability to work effectively with global, virtual teams
  • High degree of initiative and self-motivation
  • Ability to manage multiple priorities successfully
  • Team-oriented, with a focus on achieving team goals
  • Strong presentation and public speaking skills

Skills

  • serverless
  • Tensorflow
  • PyTorch
  • ml-flow
  • mlflow
  • kubeflow
  • Airflow
  • apache-airflow
  • Python
  • javascript
  • amazon-web-services
  • google-cloud-platform
  • microsoft-azure
  • Docker
  • Kubernetes
  • Prometheus
  • Grafana
  • splunk
  • Hadoop
  • apache-hadoop
  • Spark
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