Senior Machine Learning Engineer

machine learningAIJavaPythonScalaNoSQLAerospikeCassandraTensorFlowPyTorchSparkMapReduceETLadtechprogrammaticdata scienceengineeringhybrid

Key details

Salary

$180K – $220K

Employment type

Full-time

Seniority

Senior

Years experience

5-10

Location

Baltimore, Maryland, United States; Bellevue, Washington, United States; Burlington, Vermont, United States; Chicago, Illinois, United States; Dallas, Texas, United States; Los Angeles, California, United States; New York, New York, United States; Redwood City, California, United States; San Carlos, California, United States; San Diego, California, United States

Full job description

The Sr. Machine Learning Engineer will join the Applied Data Science group within Nexxen DSP Software Development. This role involves building applied data science infrastructure for real-time performance optimization and machine learning solutions. Responsibilities include developing high-performance large-scale services for programmatic integrations, applying AI/ML to real-time ad scoring and bid optimization, designing ad algorithm architecture, scalable data analysis, and collaborating with cross-functional teams. Requirements include a Bachelor's degree in Computer Science or related field, 5+ years engineering experience, expertise in AI/ML, Java, Python, Scala, NoSQL databases (Aerospike, Cassandra), ML/DL frameworks (TensorFlow, PyTorch), data processing (Spark, MapReduce), and strong communication skills. Desired qualifications include MS or PhD, AdTech experience, and knowledge of LLM and GenAI. The position is hybrid with 3 days in New York office and remote work otherwise. Salary range in New York is $180,000 - $220,000. Benefits include medical, dental, vision, disability insurance, 401(k), EAP, parental leave, discretionary time off, and company-paid holidays.

What you'll do

Develop critical high-performance, large-scale services for Nexxen DSP Programmatic integrations and Platform product
Drive ground-breaking innovation and apply state-of-the-art AI and machine learning in real-time ad scoring and ranking system for bid optimization
Invent and iterate novel solutions for complex ad challenges with fast turnaround
Lead the ad algorithm architecture design and iteration of the advertising system
Develop scalable and efficient approaches for large-scale data analysis and model development
Build and experiment with new algorithms and models end-to-end, from production rollout to continuous optimization
Collaborate with data scientists, engineering teams, product managers, and program managers in an open and creative environment
Help troubleshoot production and customer issues
Follow agile methodologies and work in a fast-paced environment

Requirements

Bachelor's in Computer Science or a related field of study
5+ years of engineering experience working at leading technology companies
History of successfully taking ownership of features/functionality and delivering end-to-end projects
Strong knowledge of and experience implementing AI/ML technologies, mathematics, and statistics
Expertise in Java, Python, and Scala
In-depth knowledge of data structures and algorithms
Practical experience working with large NoSQL databases like Aerospike and Cassandra
Interest in ad campaign optimization and iterative model updates
Experience building applications on top of large-scale ML/DL frameworks (TensorFlow, PyTorch)
Expertise working with data processing tech stack (Spark, MapReduce)
Expertise in building data-driven services and applications (ETL)
Experience with interdisciplinary collaborations with Data Science, Product, and Business stakeholders
Proven track record of thriving in a fast-paced, data-driven, and collaborative work environment
Strong communication skills with an ability to communicate complex concepts to non-technical stakeholders

Tech stack

JavaPythonScalaAerospikeCassandraTensorFlowPyTorchSparkMapReduce

Benefits

Medical insuranceDental insuranceVision insuranceDisability insurance401(k)Employee Assistance Program (EAP)Parental leaveDiscretionary time offCompany-paid holidays