Software Developer

Key Skills

Aartificial intelligence, Analytical and Problem solving, C++, Cloud computing, Data Modeling, Data Visualization, Deep Learning, Keras software library, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), NoSQL, NumPy, Pandas, Reinforcement Learning, REST API, Software Development, TensorFlow, Transformer

Job Description

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

Responsible for designing, developing, and implementing artificial intelligence (AI) and machine learning (ML) solutions. He/She will work on creating and optimizing algorithms, models, and systems to solve complex problems and enhance business processes. He/She should collaborate with cross-functional teams, including data scientists, software engineers, and domain experts, to deliver innovative AI-powered solutions.

Job Description

We’re looking for an experienced developer with artificial intelligence engineer experience to join our innovation team. The developer will be using deep learning, NLP, computer vision, chatbots, and robotics to help us improve various business outcomes and drive innovation. The developer will join a multidisciplinary team helping to shape our AI strategy and showcasing the potential for AI through early-stage solutions. This is an excellent opportunity to take advantage of emerging trends and technologies and make a real-world difference.

Objectives of this role

• Part of research and development to meet the needs of our team’s AI strategy
• Understand our business and operational challenges and propose how integrating AI capabilities can help lead to solutions
• Part of cross-functional teams in identifying and prioritizing key areas of a partner’s business where AI solutions can drive significant business benefit
• Analyze and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards
• Create use cases with respect to domain for solving a business problem
• Responsibilities
• Work on functional design, process design (including scenario design, flow mapping), prototyping, testing, training, and defining support procedures, in collaboration with an development team and executive leadership
• Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation
• Conducting assessments of the AI and automation market and vendor landscape
• Serve as liaison between stakeholders and project teams, delivering feedback and enabling team members to make necessary changes in product performance or presentation
• Advise executives and leadership on a broad range of technology, strategy, and implementation issues associated with AI

Required skills and qualifications

• Bachelor’s or master’s degree in computer science or related field
• Three or more years of experience in applying AI to practical technology solutions
• Hands on experience with ML, deep learning, Transformers, Auto Encoders, Keras, TensorFlow, Python, NLP
• Experience on end to end ML models deployment in production.
• Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns
• Experience in REST API development, NoSQL database design, and RDBMS design and optimizations
• Processing, cleansing, and verifying the integrity of data used for analysis
• Experience with cloud environments
• Experience using data visualization tools
• Preferred skills and qualifications
• Experience in IBM Cloud and AI technologies
• Understanding and implementation of Foundation / large language models

Required Technical and Professional Expertise

• Machine Learning and Deep Learning: Solid understanding of machine learning algorithms, including supervised and unsupervised learning, as well as experience with deep learning frameworks (e.g., Watson, Keras, TensorFlow, PyTorch) and architectures (e.g., neural networks, convolutional neural networks, recurrent neural networks).
• Computer Vision: Expertise in computer vision techniques, including image classification, object detection, image segmentation, and image generation. Familiarity with libraries like OpenCV and deep learning frameworks with pre-trained models (e.g., YOLO, ResNet) is essential
• AI Frameworks and Libraries: Familiarity with popular AI frameworks and libraries, such as TensorFlow, PyTorch, Keras, scikit-learn, and NLTK (Natural Language Toolkit) for building AI models and systems.
• Data Manipulation and Analysis: Strong skills in data manipulation, preprocessing, and analysis. This includes expertise in handling large datasets, data cleaning, feature engineering, and statistical analysis.
• Data Modeling and Evaluation: Experience in developing and evaluating machine learning models, including model selection, hyperparameter tuning, and performance evaluation using appropriate metrics and techniques. Knowledge of statistical analysis and experimental design is beneficial.
• Programming Languages: Proficiency in programming languages such as Python, Java, or C++. Usage of Python extensive libraries (e.g., NumPy, pandas, scikit-learn) and frameworks for AI development.
• Software Engineering: Strong software engineering skills, including proficiency in version control systems (e.g., Git), software development methodologies, and best practices. Collaboration with software engineers to integrate AI solutions into production systems is often required.
• Problem Solving and Analytical Thinking: Strong problem-solving skills, analytical thinking, and the ability to approach complex challenges with creativity and critical reasoning. AI engineers should be able to break down problems and develop innovative solutions.
• Bachelor’s or master’s degree in computer science or related field
• Three or more years of experience in applying AI to practical technology solutions
• Hands on experience with ML, deep learning, Transformers, Auto Encoders, Keras, TensorFlow, Python, NLP
• Experience on end to end ML models deployment in production.
• Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice patterns
• Experience in REST API development, NoSQL database design, and RDBMS design and optimizations
• Processing, cleansing, and verifying the integrity of data used for analysis
• Experience with cloud environments
• Experience using data visualization tools

Preferred Technical and Professional Expertise

• Ethical and Responsible AI: Understanding the ethical implications of AI technologies and being able to design and develop AI systems with fairness, transparency, and accountability in mind is increasingly important. Knowledge of ethical AI frameworks and guidelines is beneficial.
• Reinforcement Learning: Understanding of reinforcement learning concepts and algorithms, such as Q-learning, policy gradients, and deep reinforcement learning. Experience in applying reinforcement learning to solve problems and optimize AI systems is a plus.
• Experience in IBM Cloud and AI technologies
• Understanding and implementation / tuning of Foundation / large language mode.