{"id":17093,"url":"https://alion.io/job/cerebras-applied-machine-learning-research-scientist","title":"Applied Machine Learning Research Scientist","company":{"id":31,"name":"Cerebras Systems","domain":"cerebras.ai","url":"https://alion.io/company/cerebras-systems","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":74,"open_postings":25,"ghost_share":0,"stale_share":0.84,"repost_share":0,"time_to_fill_p50_days":86,"computed_at":"2026-10-19T05:45:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":184000,"max_usd":347000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":451},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Cerebras","optional":false},{"name":"Edge AI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"GRPO","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"RLHF","optional":false},{"name":"Synthetic Data","optional":false},{"name":"FSDP","optional":true},{"name":"Megatron-LM","optional":true}],"status":"live","first_seen_at":"2026-03-05T22:03:05Z","employer_posted_date":"2026-03-05","last_verified_at":"2026-10-19T06:52:15Z","board_verified":true,"closed_at":null,"days_open":227,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":227},"description":"Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services. \nThis order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.\nCerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.\nAbout The Role\nAs an Applied Machine Learning Research Scientist at Cerebras, you will play a key role in turning modern machine learning techniques into scalable, high-performance systems. This role sits at the intersection of modeling and systems focused not on publishing new algorithms, but on understanding how they work and making them run effectively at scale. Your work will directly impact how large language models (LLMs) are trained, optimized, and deployed on one of the most advanced AI platforms in the world.\nYou will work closely with researchers and senior engineers to implement and improve workflows for LLM pretraining, fine-tuning, and reinforcement learning-based post-training. This includes building training pipelines, debugging complex system behaviors, improving model quality, and iterating on data and evaluation strategies. Your contributions will help translate cutting-edge ML ideas into reliable, production-ready systems that solve real-world problems.\nThis role is ideal for candidates who enjoy hands-on engineering, want to build deep intuition for ML systems, and are excited about working on LLMs and reinforcement learning in practice, not just in theory.\nResponsibilities\nApply post-training techniques (e.g. RLVR, RLHF, GRPO etc.) techniques to improve model performance.\n\nBuild and maintain evaluation pipelines to measure model performance across tasks and domains.\n\nDebug issues across the ML stack, including data pipelines, training jobs, model outputs and mixed or lower precision computation.\n\nCollaborate with researchers to translate ML ideas into efficient, scalable implementation.\n\nDesign, implement, and scale ML pipelines across all stages of LLM development (pretraining, fine-tuning, alignment).\n\nWork with large datasets, including dataset generation, filtering, and synthetic data approaches.\n\nOptimize training and inference workflows for performance, efficiency, and reliability.\n\nContribute high-quality, maintainable code to shared ML infrastructure.\n\nSkills & Qualifications\nBachelor’s or Master’s degree in Computer Science, Engineering, or a related field.\n\n4+ years of experience (including internships, research, or industry experience) working with machine learning systems; we are hiring multiple positions for various levels.\n\nStrong programming skills in Python.\n\nExperience with ML frameworks such as PyTorch.\n\nSolid understanding of machine learning fundamentals.\n\nFamiliarity with deep learning architectures, particularly transformers.\n\nAbility to read and understand modern ML papers and implement key ideas.\n\nPreferred Skills & Qualifications\nExperience working with large language models (training, fine-tuning, and evaluation).\n\nFamiliarity with reinforcement learning concepts.\n\nExperience with distributed training frameworks (e.g., FSDP, Megatron).\n\nExperience working with large-scale datasets and data pipelines.\n\nExperience debugging or optimizing ML systems for performance.\nContributions to meaningful codebases, projects, or open-source systems\n\nWhy Join Cerebras\nPeople who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:\nBuild a breakthrough AI platform beyond the constraints of the GPU.\n\nPublish and open source their cutting-edge AI research.\n\nWork on one of the fastest AI supercomputers in the world.\n\nEnjoy job stability with startup vitality.\n\nOur simple, non-corporate work culture that respects individual beliefs.\n\nFind out more about what it's like to work at Cerebras here!\nApply today and become part of the forefront of groundbreaking advancements in AI!\nCerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.\nThis website or its third-party tools process personal data. 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