Machine Learning Engineer
Job Title: Machine Learning Engineer
Location: On-Site
Company: Capital One
Industry: Artificial Intelligence, Technology, Data Science
About the Role:
Are you passionate about creating intelligent systems that learn, adapt, and solve real-world challenges? As a Machine Learning Engineer at [Company Name], you’ll be at the forefront of innovation, designing and deploying cutting-edge algorithms that power smarter decisions and transform industries.
This is more than a role—it’s an opportunity to bring your technical expertise and creative problem-solving to a team dedicated to pushing the boundaries of what’s possible with machine learning. From building scalable models to optimizing performance, you’ll play a vital role in crafting impactful solutions for our clients and users.
What You’ll Do:
- Build and Optimize Models: Design, develop, and fine-tune machine learning models for diverse applications, from recommendation engines to natural language processing.
- Deploy at Scale: Implement and integrate ML pipelines into production systems, ensuring scalability, efficiency, and reliability.
- Collaborate Across Teams: Partner with data scientists, engineers, and product teams to identify opportunities, define use cases, and deliver tailored solutions.
- Handle Big Data: Work with massive datasets, leveraging tools and platforms to preprocess, clean, and extract meaningful insights.
- Innovate with AI: Explore new algorithms, frameworks, and techniques to keep our solutions at the cutting edge of machine learning technology.
- Monitor and Improve: Continuously evaluate model performance, identify bottlenecks, and refine solutions to ensure they meet business goals.
What We’re Looking For:
- 3+ years of experience in machine learning, software engineering, or related fields, with a proven track record of deploying models in production.
- Strong programming skills in Python, R, Scala, or similar languages, with experience in machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Knowledge of data pipelines and tools like Apache Spark, Hadoop, or AWS/GCP/Azure for large-scale data processing.
- Experience with model deployment techniques, MLOps practices, and containerization tools like Docker and Kubernetes.
- Proficiency in statistical analysis, feature engineering, and performance tuning.
- Problem-solving mindset with the ability to navigate ambiguity and deliver clear, actionable solutions.
- Strong collaboration and communication skills, with a passion for teamwork and shared success.
Bonus Points:
- Experience in specialized areas like natural language processing, computer vision, or time-series analysis.
- Familiarity with reinforcement learning or advanced AI techniques.
- Hands-on experience with CI/CD pipelines and automation in ML workflows.
- Contributions to open-source projects or a portfolio of published work in AI/ML research.
- Advanced degree (M.S./Ph.D.) in Machine Learning, Computer Science, Data Science, or a related field.
Why Capital One?
- Innovative Projects: Work on groundbreaking machine learning solutions that solve real-world problems and drive meaningful impact.
- Supportive Culture: Be part of a collaborative team that values diversity, creativity, and growth.
- Flexible Work Environment: Enjoy a remote-friendly culture that prioritizes work-life balance.
- Continuous Learning: Access resources for professional development, mentorship, and certifications to stay ahead in a rapidly evolving field.
- Competitive Benefits: Receive a comprehensive package, including salary, equity options, and top-tier perks.
- Impactful Mission: Contribute to projects that transform industries and improve lives through the power of AI.
