Job Title : Senior Machine Learning Engineer

Location : New York, United States (Remote)

Job Type : Full Time

Our Client is looking for a seasoned technology leader who thrives at the intersection of modern engineering, machine learning, and enterprise-scale innovation. If you're passionate about advancing AI capabilities and driving adoption of next-generation technologies across large platforms, this role is for you.

What You’ll Do

1. Champion modernization and innovation by educating teams on emerging technologies, demonstrating real business and consumer impact, and driving adoption of high-value solutions.
2. Work on high-visibility, complex technical challenges that directly shape customer experiences and business outcomes.
3. Create a culture of trust and collaboration, balancing technical mentorship with inclusivity so diverse ideas and expertise can thrive.
4. Promote engineering excellence, identifying opportunities to streamline, reuse, or innersource scalable solutions.
5. Engage and influence stakeholders across multiple levels, translating technical strategies into clear, actionable value.
6. Serve as a trusted technology advisor, helping define strategy and build consistent patterns for platform and capability adoption.
7. Develop and grow the next generation of engineering talent, both through mentorship and strategic hiring.

Basic Qualifications

1. Bachelor’s degree
2. 7+ years of professional Software Engineering experience
3. 5+ years working with Machine Learning Systems and ML infrastructure

Preferred Qualifications

1. Master’s degree in a related field
2. 7+ years coding experience in Python, Java, Go, and SQL
3. 6+ years of deploying machine learning models into production
4. Deep understanding of scaling and operating ML workloads in production environments
5. Experience working with LLMs, including prompt engineering, fine-tuning, evaluation, and alignment practices
6. 3+ years of experience with systems such as Kafka, Spark, Airflow, AWS Glue, or Kinesis
7. Hands-on experience with Databricks or Snowflake
8. Familiarity with LLM Ops practices, including model lifecycle management, cost optimization, and performance tuning

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