Senior AI Back End developer

Introduction
At IBM work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so lets talk.

Your Role and Responsibilities

• Solution Design: Lead the design of end-to-end AI solutions that encompass data acquisition preprocessing model selection training deployment and maintenance.
• Algorithm Development: Design implement and optimize machine learning algorithms and models that solve specific business problems such as natural language processing computer vision recommendation systems predictive analytics etc.
• Data Preprocessing: Clean preprocess and curate large datasets to ensure high-quality data for training and validation of AI models.
• Model Training and Evaluation: Train and fine-tune AI models using appropriate techniques and frameworks. Evaluate model performance using relevant metrics and iterate on models to improve their accuracy and efficiency.
• Architecture Design: Create high-level architecture designs for AI systems that consider scalability performance security and integration with existing systems.
• Technical Leadership: Provide guidance and mentorship to AI developers data scientists and engineers ensuring adherence to best practices and architectural guidelines.
• Technology Evaluation: Stay updated with emerging AI technologies tools and frameworks and evaluate their suitability for solving specific business challenges.
• Collaboration: Work closely with cross-functional teams including data engineers software developers product managers and domain experts to align AI solutions with overall product development.
• Proof of Concept: Develop prototypes and proof-of-concepts to demonstrate the feasibility of proposed AI solutions and gain buy-in from stakeholders.
• Innovation: Explore innovative AI applications and propose ideas that can lead to new products features or enhancements.
• Code Development: Write clean efficient and well-documented code using programming languages such as Python and utilize libraries and frameworks like TensorFlow PyTorch scikit-learn etc.
• Ethical and Regulatory Compliance: Ensure that AI solutions meet ethical standards and regulatory requirements particularly in areas such as data privacy bias mitigation and transparency.
• Performance Optimization: Optimize AI models and system performance including latency throughput and resource utilization to meet business needs.
• Documentation: Maintain clear documentation of the AI models algorithms development processes and deployment procedures.
• To be successful you will need:
• Passion for handling technical challenges and be goal and results oriented
• Excellent communication skills and ability to work with multiple team
• Proven listening detail-oriented thinking and creative problem-solving skills
• Ability to work in highly collaborative global organization
• Be open to flexible schedule in development and support environment
• Agile development experience
• What we look for:
• Hands on experience in AI Python Java Scala and utilize libraries and frameworks like TensorFlow PyTorch strongly preferred.
• BE/B Tech in Computer Science or relevant and 17 to 20+ years track record in Architecture and development in a customer facing role working with enterprise software

Required Technical and Professional Expertise

• 7-8 years of experience in developing enterprise applications using Java Python Scala spark and related technologies with 2+ years a focus on Data Engineering DataOps MLOps
• Knowledge of data best practices and ML/Dev operations in SaaS and hybrid environments
• Software development strategies for low latency high throughput software’s
• Hands-on experience with common distributed processing tools and languages Python Spark Hive Presto
• Deep understanding of data pipelines data modelling strategies schema management
• Experience with specialized data architectures like data lake data mesh and optimizing data layouts for efficient processing.
• Hands on Experience with streaming platforms and frameworks like Kafka spark-streaming
• Strong understanding of advanced algorithms used in design and development of enterprise grade software
• Strong understanding of data governance data security and data privacy best practices.
• Strong expertise in working with distributed big data technologies and frameworks like Spark Flink or Kafka.
• Ability in managing and communicating data pipeline plans to internal clients
• Familiarity with pipeline orchestrator tools like Argo Kubeflow Airflow or other open source
• Familiarity with platforms like Kubernetes and experience building on top of the native platforms
• Excellent communication skills with the ability to effectively collaborate with technical and non-technical stakeholders
• Experience with cloud-based data platforms and services (e.g. IBM AWS Azure Google Cloud).
• Ability to provide guidance to less experienced team members.

Preferred Technical and Professional Expertise

• Experience designing building and maintaining data processing systems working in containerized environments (Docker OpenShift k8s)
• Experience working with both batch and streaming data processing pipelines using workflow engines (Argo Tekton etc.)
• Experience developing or leveraging automated platforms for data observability data quality and drift and systems to automatically identify and correct data issues.