AI Engineer
Role details
Job location
Tech stack
Job description
We're looking for a skilled and curious AI Engineer to join our growing team. In this role, you'll design, develop, and deploy machine learning models and AI-driven systems that power our products and services. You'll work closely with data scientists, software engineers, and product teams to bring intelligent features to life-whether that's building NLP pipelines, optimizing recommendation systems, or applying cutting-edge research to real-world challenges.
This is a hands-on role where you'll contribute across the entire ML lifecycle, from data preprocessing and model training to production deployment and performance tuning. If you're excited about solving complex problems with AI and thrive in a fast-paced, collaborative environment, we'd love to hear from you.
Responsibilities:
- Model Development: Design, develop, and deploy AI and machine learning models to solve business challenges.
- Data Analysis: Work with large datasets to extract insights and train machine learning models.
- Algorithm Implementation: Implement and optimize algorithms for AI applications, ensuring efficiency and scalability.
- Research: Stay up-to-date with the latest advancements in AI and machine learning, and apply these to ongoing projects.
- Collaboration: Collaborate with data scientists, software engineers, and other stakeholders to integrate AI solutions into products and services.
- Testing and Validation: Test and validate AI models to ensure accuracy, robustness, and reliability.
- Deployment: Manage the deployment of AI models in production environments, monitoring performance and making necessary adjustments.
- Documentation: Document AI models, processes, and findings for future reference and reproducibility.
- Performance Monitoring: Continuously monitor and evaluate AI models to improve their performance over time.
- Innovation: Identify opportunities to innovate and improve existing AI solutions and processes., Progression Opportunities As an AI Engineer, you'll have a well-supported growth path with opportunities to deepen your technical expertise and expand your impact across projects and teams. Depending on your interests, you can progress into more advanced roles such as Senior AI Engineer, AI Solutions Architect, Machine Learning Lead, or Technical Product Owner for AI initiatives.You'll be encouraged to take ownership of increasingly complex systems, contribute to strategic AI decisions, and mentor junior team members. We support certifications, attendance at industry events, and the freedom to explore new tools and approaches that shape the future of our AI capabilities.
Company Culture
Our culture is built on openness, learning, and shared purpose. We encourage collaboration across disciplines and believe diverse thinking leads to stronger, more innovative outcomes. Everyone here contributes to our direction, and we aim to make sure every voice is heard and valued.
Requirements
Do you have a Master's degree?, * Educational Background: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Experience: Minimum of 3 years of experience in AI engineering or a related role.
- Technical Skills: Proficiency in programming languages such as Python, R, or Java. Experience with AI frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Machine Learning Knowledge: Strong understanding of machine learning algorithms, neural networks, and deep learning techniques.
- Analytical Skills: Excellent analytical and problem-solving skills, with the ability to work with complex datasets.
- Communication Skills: Strong written and verbal communication skills, with the ability to explain AI concepts to non-technical stakeholders.
- Team Collaboration: Proven experience working in a collaborative, team-oriented environment.
- Project Management: Ability to manage multiple projects and meet deadlines effectively.
- Attention to Detail: High level of accuracy and attention to detail.
Desired Criteria
- Advanced Expertise: Experience with deploying AI models in production environments and optimizing for scalability and performance.
- Innovative Mindset: Passion for staying up-to-date with the latest AI research and emerging technologies, and applying them creatively to solve business challenges.
- Data Engineering: Familiarity with data pipelines, ETL processes, and working knowledge of databases and big data technologies.
- Software Development Practices: Experience with version control (e.g., Git), containerization (Docker), and CI/CD pipelines in an AI context.
- Domain Knowledge: Exposure to industry-specific applications of AI (e.g., healthcare, finance, or e-commerce) is a plus.
- Mentorship: Ability and willingness to mentor junior engineers and contribute to a culture of continuous learning.
- Problem Framing: Strong skills in translating ambiguous business problems into clear AI-driven solutions.
- Adaptability: Comfortable working in a fast-paced, agile environment with evolving priorities.
- Ethical AI Awareness: Understanding of AI ethics, bias mitigation, and responsible AI deployment principles.
Benefits & conditions
- Competitive salary
- Health and wellness benefits
- Professional development opportunities
- Collaborative and innovative work environment