AI Software Engineer (The Intelligent Systems Developer)

Are you passionate about building intelligent systems that can learn, adapt, and solve complex problems? Do you thrive on the challenge of creating AI-driven software that pushes the boundaries of what’s possible in automation, decision-making, and predictive analytics? If you’re excited about designing AI systems that drive business value and make an impact, then our client has the perfect opportunity for you. We’re looking for an AI Software Engineer (aka The Intelligent Systems Developer) to create, deploy, and optimize AI solutions that power the next generation of smart applications.

As an AI Software Engineer at our client, you’ll collaborate with data scientists, software engineers, and product teams to design and develop AI-driven applications that leverage machine learning, natural language processing (NLP), and computer vision. Your expertise will be instrumental in turning data into actionable insights, developing models, and deploying scalable AI systems into production.

Key Responsibilities:

1. Design and Develop AI Algorithms:
• Develop, implement, and optimize AI algorithms that solve complex problems. You’ll work on a wide range of AI applications, including machine learning models, deep learning frameworks, and NLP solutions, using tools like TensorFlow, PyTorch, and Scikit-learn.
2. Build Scalable AI Systems:
• Architect and build AI systems that are scalable, reliable, and maintainable. You’ll integrate AI models into production environments, ensuring smooth deployment and integration with existing software platforms, whether in the cloud or on-premise.
3. Data Pipeline Design and Integration:
• Collaborate with data engineers to build robust data pipelines that feed machine learning models. You’ll ensure that data preprocessing, feature extraction, and model training are optimized for performance and scalability.
4. Model Training and Tuning:
• Train machine learning models on large datasets, fine-tuning hyperparameters and experimenting with different architectures to improve accuracy. You’ll use techniques like cross-validation, regularization, and feature engineering to enhance model performance.
5. Collaborate with Cross-Functional Teams:
• Work closely with product managers, data scientists, and software engineers to understand business needs and deliver AI-driven solutions that align with product goals. You’ll contribute to the overall software architecture and ensure that AI systems are aligned with business requirements.
6. Deploy and Monitor AI Models:
• Deploy AI models into production environments and set up monitoring systems to track performance, detect drift, and retrain models when needed. You’ll ensure that AI models remain accurate, efficient, and maintain high performance over time.
7. Stay Updated with AI Research and Trends:
• Stay current with the latest advancements in AI research and industry trends. You’ll experiment with new algorithms, tools, and frameworks to continually improve the capabilities of AI systems and bring innovation into the company’s solutions.

Requirements

Required Skills:

• AI and Machine Learning Expertise: Strong experience in developing machine learning models, deep learning algorithms, and NLP solutions. You’re comfortable with tools and frameworks like TensorFlow, PyTorch, Scikit-learn, and Keras.
• Programming and Software Development: Proficiency in programming languages such as Python, R, or Java, with experience in developing production-level AI software. You can write clean, efficient, and maintainable code.
• Data Engineering and Pipelines: Expertise in building data pipelines for training and deploying machine learning models. You’re skilled in handling large datasets, data preprocessing, and optimizing data flows for performance.
• Model Deployment and Integration: Experience deploying AI models into production environments using cloud platforms (AWS, GCP, Azure) or on-premise infrastructure. You’re familiar with containerization tools like Docker and orchestration tools like Kubernetes.
• Collaboration and Communication: Excellent communication skills, with the ability to work across teams and explain complex AI concepts to both technical and non-technical stakeholders.

Educational Requirements:

• Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, or a related field. Equivalent experience in AI software development is also highly valued.
• Certifications or additional coursework in AI, machine learning, or data science are a plus.

Experience Requirements:

• 3+ years of experience in AI software development, with hands-on experience designing and deploying AI models into production environments.
• Proven track record of building machine learning or deep learning models, working with large datasets, and optimizing AI systems for performance and scalability.
• Experience working with cloud-based AI services (AWS SageMaker, Google AI Platform) is highly desirable.

Benefits

• Health and Wellness: Comprehensive medical, dental, and vision insurance plans with low co-pays and premiums.
• Paid Time Off: Competitive vacation, sick leave, and 20 paid holidays per year.
• Work-Life Balance: Flexible work schedules and telecommuting options.
• Professional Development: Opportunities for training, certification reimbursement, and career advancement programs.
• Wellness Programs: Access to wellness programs, including gym memberships, health screenings, and mental health resources.
• Life and Disability Insurance: Life insurance and short-term/long-term disability coverage.
• Employee Assistance Program (EAP): Confidential counseling and support services for personal and professional challenges.
• Tuition Reimbursement: Financial assistance for continuing education and professional development.
• Community Engagement: Opportunities to participate in community service and volunteer activities.
• Recognition Programs: Employee recognition programs to celebrate achievements and milestones.