Machine Learning Engineer, MadHive
$200-250k
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
$200-250k
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
- Minimum of 5+ years of experience in maintaining scalable, resilient backend systems, with around 3 years experience developing production-level deep learning models
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. Ph.D. is a plus
- "T"-shaped engineer with competency across a broad range of technologies and deep expertise in at least one technical domain
- Experience of core ML technologies such as TensorFlow, BigQuery, Bigtable, Dataflow, Kubernetes, and TFX Serving with the ability to utilize thise in our backend systems
- Proficiency in data manipulation, feature engineering, and model development
- Proficiency in deep learning frameworks
- Strong ownership mentality and a passion for staying at the cutting edge of technology
- Ability to autonomously manage complex scopes of work and deliver product-grade code with minimal guidance
- Collaborative mindset, ability to synthesize and distill information across diverse perspectives, and effective cross-departmental collaboration skills
- Background diversity is encouraged; previous experience in adtech is not mandatory
What the job involves
- Madhive is seeking a Machine Learning Engineer to assume a pivotal role in the development and deployment of cutting-edge machine learning models and algorithms that drive our products and services
- In this role, you will collaborate closely with cross-functional teams to design, construct, and implement machine learning solutions that directly impact our business success
- As a Machine Learning Engineer, you'll be at the forefront of technology, working on diverse projects that align with your interests, abilities, and development goals
- Develop machine learning models that predict, classify, and generate data to enhance various facets of our platform, including sophisticated bidding strategies, search functionalities, and user experience enhancements
- Oversee MLOps processes, ensuring visibility into model performance, facilitating Canary and Red/Green model deployments, and managing retraining and fine-tuning efforts
- Develop and implement machine learning models and algorithms that address specific business problems and requirements
- Collect, preprocess, and clean large datasets to ensure data quality and usability for training machine learning models
- Create and engineer relevant features to improve model performance and accuracy
- Train, fine-tune, and optimize machine learning models using various techniques, including deep learning, reinforcement learning, and ensemble methods
- Evaluate the performance of machine learning models using appropriate metrics and conduct A/B testing to validate their effectiveness
- Collaborate with DevOps and software engineering teams to deploy machine learning models into production environments
- Monitor model performance in production, implement model updates, and address any issues that arise
- Stay up-to-date with the latest advancements in machine learning and artificial intelligence and apply them to solve real-world problems
- Maintain comprehensive documentation of models, datasets, and code to ensure knowledge sharing and reproducibility
- Work closely with data scientists, software engineers, and product managers to align machine learning efforts with business goals and requirements
- Leverage Google Cloud Platform (GCP) as our exclusive infrastructure provider, while also collaborating with a language-agnostic engineering team
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.
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