Machine Learning Engineer (Remote - US) at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

25 Jan, 26

Salary

173200.0

Posted On

27 Oct, 25

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI, Python, Data Pipelines, Model Evaluation, Prompt Design, Agentic AI, Memory Management, Quality Assurance, Cross-Functional Collaboration, Observability, Reliability, Efficiency, ML Infrastructure, LLM Concepts, Communication Skills

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Machine Learning Engineer in the United States. As a Machine Learning Engineer, you will design, implement, and optimize intelligent AI systems that process large-scale, heterogeneous machine data. You will work on cutting-edge agentic AI solutions, combining machine learning, prompt engineering, and rigorous evaluation to develop autonomous AI agents that deliver actionable insights in real time. Collaborating closely with product, data, and infrastructure teams, you will ensure high reliability, performance, and observability of deployed models. This role offers the opportunity to define best practices in AI context engineering and contribute to innovative AI infrastructure while working in a high-impact, fast-paced environment. You will have the autonomy to drive projects, experiment with novel approaches, and directly shape the next generation of AI capabilities. Accountabilities Design, develop, and optimize agentic AI components, including context engineering, memory management, and prompt design. Build and maintain high-quality datasets, including sourcing strategies, vendor coordination, and quality assurance at scale. Prototype, evaluate, and iterate on novel reasoning strategies to ensure model reliability, interpretability, and performance. Collaborate with cross-functional teams to deliver end-to-end AI-powered insights and solutions. Monitor, test, and improve deployed AI agents to maintain observability, reliability, and efficiency. Operate autonomously to define project scope, set milestones, and deliver outcomes in a dynamic environment. B.Tech, M.Tech, or Ph.D. in Computer Science, Data Science, or related fields. 1–2 years of industry experience in machine learning or AI, demonstrating ownership and successful project delivery. Strong understanding of machine learning fundamentals, data pipelines, and model evaluation. Proficiency in Python and ML/data libraries (NumPy, pandas, scikit-learn); familiarity with JVM languages is a plus. Knowledge of LLM concepts, prompt design, and agentic AI frameworks. Excellent communication skills and a passion for shaping emerging AI paradigms. Desired: Experience deploying AI agents or LLM applications in production, ML infrastructure tools (PyTorch, MLflow, Airflow, Docker, AWS), and exposure to LLM Ops including observability, latency, and cost monitoring. 💰 Competitive salary range: $148,000–$173,200, adjusted based on experience, skills, and location. 🏥 Comprehensive health, dental, and vision coverage. 🌴 Paid time off and flexible leave policies. 📈 Retirement savings and financial planning options. 💻 Remote work opportunities with flexibility for work-life balance. 📊 Access to cutting-edge AI tools and high-impact projects. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the three candidates who best match the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or assessments) are managed by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

Design, implement, and optimize intelligent AI systems that process large-scale machine data. Collaborate with product, data, and infrastructure teams to ensure high reliability and performance of deployed models.