Firsthand · 6 days ago

Senior/Staff Machine Learning Engineer

New York

Full-time

Onsite

Senior Level

$120K/yr - $240K/yr

5+ years exp

Wonder how qualified you are to the job?

Artificial Intelligence (AI)Information Technology

Insider Connection @Firsthand

Discover valuable connections within the company who might provide insights and potential referrals, giving your job application an inside edge.

Responsibilities

Pioneering experimenting, developing, and deploying cutting-edge machine learning and large language models for production systems.

Responsible for the full life-cycle of ML systems. Monitor and evaluate the performance of machine learning models, constantly proposing and implementing enhancements as required.

Staying ahead of the game by embracing the latest breakthroughs in machine learning and proactively applying them to amplify the prowess of our systems.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

PythonMachine LearningSoftware EngineeringML FrameworksML ExperimentsMLOps ToolsNLPLLMModel Fine-TuningReward LearningSQLData WranglingAWSGCPCloud PlatformsProblem-SolvingAttention to DetailCommunicationCollaborationSelf-DrivenHighly Motivated

Required

5+ years of professional work experience in the Machine Learning field.

Solid comprehension of software engineering fundamentals. Proficiency in Python, ML frameworks, ML experiments, and MLOps tools.

In-depth knowledge and experience with machine learning systems in production, particularly in the NLP/LLM field. Used LLM beyond hobbies. Had experiences in model fine-tuning and/or reward learning.

Strong analytical and problem-solving skills, coupled with an unwavering attention to detail.

Hands-on experience with data wrangling using SQL and other tools.

Familiarity with major cloud platforms (e.g., AWS, GCP).

Exceptional communication and collaboration abilities.

Self-driven and highly motivated to take ownership of projects and drive them to completion.

Thrive in a startup environment with a high degree of freedom and ambiguity.