AI Engineer (The AI Architect) - Unreal Gigs

Introduction:

Are you passionate about building intelligent systems that can analyze data, make predictions, and automate decision-making? Do you love solving complex challenges and applying cutting-edge machine learning techniques to create AI-powered solutions that deliver real-world impact? If you’re excited about designing and developing AI systems that push the boundaries of technology, then our client has the perfect opportunity for you. We’re looking for an AI Engineer (aka The AI Architect) to design, develop, and deploy AI models and solutions that will transform industries.

As an AI Engineer at our client, you’ll work at the forefront of AI innovation, collaborating with data scientists, software developers, and product teams to integrate advanced machine learning models into products and services. Your expertise will be key in turning raw data into actionable insights, driving automation, and improving business outcomes with AI-driven solutions.

Key Responsibilities:

1. Develop and Deploy AI Models:
• Design, build, and deploy machine learning and AI models, including supervised and unsupervised learning techniques. You’ll work on projects involving natural language processing (NLP), computer vision, predictive analytics, and more, using frameworks like TensorFlow, PyTorch, or Scikit-learn.
2. Data Processing and Feature Engineering:
• Collaborate with data engineers and scientists to collect, preprocess, and transform large datasets for model training. You’ll ensure that data pipelines are optimized for AI workflows and support the development of high-performance models.
3. Optimize Model Performance:
• Experiment with different model architectures, algorithms, and hyperparameters to improve accuracy, speed, and scalability. You’ll apply techniques like cross-validation, regularization, and gradient boosting to fine-tune models and ensure they perform well in production.
4. Deploy Models into Production:
• Work with DevOps and software engineering teams to deploy AI models into production environments, ensuring they are scalable, efficient, and integrated with other systems. You’ll build APIs and services that make your models accessible for real-time applications.
5. Monitor and Retrain AI Models:
• Continuously monitor the performance of deployed models, detecting model drift and updating models as necessary. You’ll retrain models with new data to keep them accurate and relevant in changing environments.
6. Collaborate with Cross-Functional Teams:
• Work closely with product managers, engineers, and other stakeholders to understand business needs and translate them into AI solutions. You’ll ensure that AI models align with product goals and deliver measurable business outcomes.
7. Stay Up-to-Date with AI Research and Trends:
• Keep current with the latest advancements in machine learning, AI algorithms, and frameworks. You’ll experiment with new technologies and bring innovative approaches to solving AI challenges within the organization.

Requirements

Required Skills:

• AI and Machine Learning Expertise: Deep understanding of machine learning algorithms, such as decision trees, neural networks, clustering, and reinforcement learning. You’re experienced in developing models for NLP, computer vision, and predictive analytics.
• Programming and AI Tools: Proficiency in programming languages like Python or R, and experience using machine learning frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn. You’re comfortable with coding and debugging AI solutions.
• Data Engineering and Feature Engineering: Hands-on experience with data preprocessing, feature selection, and engineering for AI models. You know how to clean and transform large datasets to support machine learning workflows.
• Deployment and Integration: Experience deploying AI models into production environments using cloud platforms (AWS, GCP, Azure) and containerization tools like Docker and Kubernetes. You know how to integrate models into existing systems and optimize for scalability.
• Collaboration and Communication: Strong collaboration skills, with the ability to work with cross-functional teams, including data scientists, engineers, and product managers. You can clearly communicate technical concepts to non-technical stakeholders.

Educational Requirements:

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

Experience Requirements:

• 3+ years of experience in AI engineering or machine learning, with hands-on experience developing and deploying AI models in real-world applications.
• Proven track record of working with large datasets, designing machine learning pipelines, and delivering AI-driven solutions that solve business problems.
• Experience with cloud-based AI services (AWS SageMaker, Google AI Platform, Azure ML) 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.