Machine Learning Engineer, Infrastructure
Description For Machine Learning Engineer, Infrastructure
Attentive, a leading AI-powered mobile marketing platform, is seeking a Machine Learning Engineer for their Infrastructure team. This role combines sophisticated ML engineering with robust infrastructure development, offering an opportunity to work on cutting-edge personalization technology that serves major global brands like Neiman Marcus, Samsung, Wayfair, and Dyson.
The position requires expertise in both machine learning and infrastructure, with responsibilities spanning from model development to production deployment. You'll be working with modern ML frameworks, cloud platforms, and infrastructure tools while collaborating with cross-functional teams to deliver scalable ML solutions.
The role offers a hybrid work arrangement in San Francisco, with competitive compensation ranging from $212,000 to $318,000, plus substantial equity and comprehensive benefits. This is an excellent opportunity for experienced ML engineers who want to impact how brands engage with consumers through AI-driven personalization.
The company has been recognized by Deloitte's Fast 500, LinkedIn's Top Startups, and Forbes Cloud 100, indicating strong growth and stability. You'll be joining a company that values diversity, maintains an inclusive workplace, and offers various employee resource groups through their AWAKE initiative.
Key technical requirements include 3 years of experience with ML frameworks, Python, statistical models, and complex algorithm development, plus 2 years of experience with Kubernetes and AWS EKS. The role combines technical depth with business impact, making it ideal for those seeking to advance their career in machine learning engineering.
Responsibilities For Machine Learning Engineer, Infrastructure
- Develop and implement Machine Learning models including design, development and deployment
- Train, evaluate and optimize models to ensure high performance
- Build and maintain Machine Learning Infrastructure
- Implement and manage scalable machine learning systems on cloud platforms
- Perform data exploration and analysis
- Query, clean, and manipulate data with SQL and Pandas
- Monitor the performance of deployed models
- Work closely with product managers, software engineers and data scientists
- Maintain documentation of processes, results and systems
- Ensure models comply with data privacy and ethical standards
Requirements For Machine Learning Engineer, Infrastructure
- Bachelor's degree in Computer Science, Data Science, Computer Engineering, Mathematics, Statistics, or related field
- 3 years of experience with machine learning frameworks (Pytorch, Tensorflow, Pandas, Numpy, Sci-kit learn)
- 3 years of experience with Python and statistical models
- 3 years of experience working with cross-functional teams
- 3 years of experience developing complex algorithms
- 2 years of experience deploying and managing ML models with Kubernetes and AWS EKS
- 2 years of experience deploying advanced machine learning models and running AB tests
Benefits For Machine Learning Engineer, Infrastructure
- Competitive salary + equity + benefits
- Health & wellness benefits
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