Staff Engineer, MadHive
Machine Learning
Advertising solution leveraging cryptography and machine learning
Job no longer available
Advertising solution leveraging cryptography and machine learning
201-500 employees
Job no longer available
201-500 employees
Company mission
To take complex, cutting-edge technology and turn it into intuitive, easy-to-use solutions that empower local media buyers.
Role
Who you are
- 10+ years of experience in building internet-scale robust backend systems with a specialization of around 5 years experience in machine learning model development and deployment
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. Ph.D. is a plus
- Experience with core ML technologies such as TensorFlow, JAX, BigQuery, Bigtable, Dataflow, Kubernetes, and TFX Serving with the ability to utilize these in our backend systems
- Strong understanding of machine learning algorithms, deep learning, and neural networks
- Experience with data preprocessing, feature engineering, and model evaluation techniques
- Ability to leverage Google Cloud Platform (GCP) as our exclusive infrastructure provider, while also collaborating with a language-agnostic engineering team
- Strong communication and collaboration skills
- Experience mentoring junior engineers and supporting the hiring and evaluation of candidates
What the job involves
- We are seeking a highly skilled and experienced Staff Machine Learning Engineer
- In this role, you will lead and contribute to developing and implementing machine learning models and algorithms to drive innovation and improve our products and services
- As a Staff Machine Learning Engineer, you’ll work on various projects based on the intersection of your affinities, abilities, and development goals
- Lead the design, development, and optimization of machine learning models and algorithms for various facets of our platform, including sophisticated bidding strategies, search & data retrieval functionalities, and user experience enhancements
- Work closely with data engineers and data scientists to gather and preprocess data, ensuring its quality and relevance for model training
- Identify and create meaningful features from raw data to enhance model performance and accuracy
- Develop robust evaluation metrics and methodologies to assess the performance of machine learning models and fine-tune them as needed
- Collaborate with DevOps and software engineering teams to deploy machine learning models into production environments, ensuring scalability and reliability
- Stay up-to-date with the latest advancements in machine learning and AI research, and apply innovative techniques to solve complex problems
- Provide guidance and mentorship to junior machine learning engineers, helping them grow their skills and capabilities
- Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and domain experts, to understand business requirements and deliver effective solutions
- Maintain clear and organized documentation of machine learning models, algorithms, and processes for knowledge sharing and future reference
- Participate in an on-call rotation schedule to provide timely response and support for engineering-related issues outside of regular business hours, ensuring the continuous operation of critical systems and infrastructure
Our take
The rise in streaming content has revolutionized digital advertising, offering advertisers the potential for more precise campaign calibration. However, alongside this opportunity come new challenges such as consumer overload, ad fraud, and data privacy concerns, compounded by the need to integrate with traditional linear television. Navigating these complexities requires a comprehensive solution, and that's where MadHive steps in.
Utilizing AI technology, MadHive's video ad software suite tackles these challenges head-on. It intelligently identifies optimal ad placements, manages ad frequency to prevent saturation, and gauges consumer intent across various platforms including web, mobile, and TV. This capability allows advertisers to execute nationwide campaigns with pinpoint local targeting - a remarkable achievement in the dynamic digital content landscape.
Unsurprisingly, MadHive boasts an impressive client roster, boasting a 95% renewal rate with major names like Fox, McAfee, and Tegna Premion. This consistent satisfaction has propelled MadHive to expand its offering into critical areas such as data privacy. For instance, its $100M contract with Google Cloud not only enhances its security measures but also equips it with capabilities that smaller competitors will struggle to match.
Steph
Company Specialist at Welcome to the Jungle
Insights
36% employee growth in 12 months
Company
Funding (last 2 of 3 rounds)
Jun 2023
$300m
LATE VC
Aug 2018
$3m
EARLY VC
Total funding: $306.4m
Company benefits
- 401(K) Matching
- Company Equity
- Retirement Plans
- Performance Bonuses
- Competitive Pay
- 100% Company-Covered Health Insurance
- Dental Benefits
- Vision Benefits
- Generous Maternity and Paternity Leave
- Paid Holidays
- Unlimited Vacation
- Free Lunch In-Office
- Commuter Benefits
Company HQ
Tribeca, New York, NY
Leadership
Jim Wilson
(CEO)Prior to joining Madhive in 2024, Jim was the CEO of North America for Talon.
Thomas Tidgwell
(CFO)Prior to joining Madhive in 2021, Thomas was a VP of Corporate Development & FP&A at WarnerMedia.
Share this job
View 8 more jobs at MadHive