Video
No H1
Local
Onsite
AI/Machine Learning Engineers to join our team in Chicago, IL. We have several upcoming projects across diverse industries, from finance to healthcare and consumer goods, offering a challenging and rewarding environment for candidates passionate about AI and machine learning.
The role involves designing, developing, and deploying advanced AI models and machine learning algorithms that drive innovative solutions to real-world problems. Ideal candidates will have expertise in deep learning, natural language processing, and computer vision, and the ability to collaborate with cross-functional teams to turn research into production-ready systems.
If you're someone with a passion for data, a keen interest in building intelligent systems, and a knack for solving complex problems, we want to hear from you!
Key Responsibilities
- Algorithm Development: Design and implement cutting-edge machine learning models and AI algorithms tailored to solve complex problems in various domains such as finance, healthcare, and retail.
- Data Preprocessing: Extract, clean, and preprocess large datasets from diverse sources to prepare them for training and inference.
- Model Training & Evaluation: Train, fine-tune, and optimize deep learning models (such as CNNs, RNNs, and transformers) using large datasets; evaluate model performance using appropriate metrics.
- Deployment & Monitoring: Collaborate with software engineers to integrate machine learning models into production systems and monitor their performance to ensure accuracy and scalability.
- Research & Innovation: Stay up-to-date with the latest AI research and advancements, experiment with novel architectures, and evaluate their potential for real-world applications.
- Cross-Functional Collaboration: Work closely with data scientists, software engineers, and product managers to develop AI solutions that meet client requirements and business goals.
- Documentation & Reporting: Maintain comprehensive documentation of all models, workflows, and experimental setups, and present findings and recommendations to both technical and non-technical stakeholders.
- Mentoring: Guide junior team members and share expertise in AI/ML techniques and best practices.
Required Qualifications - Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Mathematics, or related fields. PhD is a plus.
- Experience:
- Minimum of 3-5 years of hands-on experience in AI and machine learning model development.
- Strong portfolio showcasing successful AI projects.
- Technical Skills:
- Proficiency in Python, R, or Java.
- Experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, or MXNet.
- Solid understanding of data structures, algorithms, and complexity analysis.
- Experience with cloud platforms like AWS, Google Cloud, or Azure.
- Strong knowledge of NLP (Natural Language Processing), computer vision, and recommendation systems.
- Experience working with large-scale datasets and data pipelines using tools such as Apache Spark, Hadoop, or SQL.
- Knowledge of reinforcement learning, GANs (Generative Adversarial Networks), and transfer learning is highly preferred.
- Soft Skills:
- Excellent problem-solving abilities and analytical thinking.
- Strong communication skills for both technical and non-technical audiences.
- Ability to work both independently and collaboratively in a fast-paced environment.
Nice-to-Have
- Experience in AI-driven software applications in industries like healthcare, finance, or e-commerce.
- Familiarity with DevOps, CI/CD pipelines, and containerization technologies like Docker or Kubernetes.
- Published research or participation in notable AI conferences/competitions (e.g., NeurIPS, ICML, Kaggle).