Top Software Engineer Jobs in NYC, NY
The Director of Machine Learning Operations at Kargo will lead and shape the ML Operations function, managing a team to develop and implement ML Ops strategies. Responsibilities include overseeing the deployment and maintenance of machine learning models and collaborating with cross-functional teams to integrate ML solutions into the advertising technology platform.
As a Software Engineer II at Kargo, you will work on systems that handle ad requests, iterate on video ad delivery, collaborate with a team on full stack development, and contribute to the agile environment. Qualifications include 3+ years of software engineering experience, understanding of SDLC, experience with automated testing, and strong command of programming languages like Golang, JavaScript, NodeJS, PHP, and Python.
Responsible for building and improving cloud infrastructure, managing continuous integration tools, deploying data streaming solutions, and identifying new technologies to enhance infrastructure stack at Kargo.
As a Senior Software Engineer at Kargo, you will take a leading role in building and optimizing contextual and identity targeting solutions within the advertising auction platform. Responsibilities include mentoring, writing clean code, working on both frontend and backend, and participating in architecture planning and code reviews.
Kargo is looking for a Senior Analytics Engineer with 5+ years of experience in data engineering. The role involves designing ETL pipelines, implementing dbt, ensuring data quality, and mentoring junior engineers. The position is based in New York, NY for a full-time in-office hybrid job.
Design, develop, and deploy machine learning models to address various business needs. Collaborate with cross-functional teams to integrate ML solutions into advertising technology platform. Monitor and optimize deployed models. Manage ML infrastructure and tools. Stay updated on industry trends and technologies.
Kargo is looking for a Data Engineer to join their Targeting and Audiences team. The role involves evaluating existing methodologies, experimenting with new solutions, and building scalable data processes. Responsibilities include maintaining identity and contextual data, expanding targeting capabilities, performing analytics, and building data pipelines. Proficiency in Airflow, Snowflake, Python, SQL, and experience with petabytes of data are required.
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