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Gramian Consulting
Gramian Consulting
KonsultācijasLoģistikaMārketings
Gramian Consulting ir attālinātam darbam prioritāti piešķirošs konsultāciju uzņēmums, kas koncentrējas uz inženierzinātņu, datu un mākslīgā intelekta talantiem. Tas palīdz organizācijām paplašināt tehniskās iespējas, nodrošinot talantu piesaisti, personāla atlasi, specializētas komandas un līgumdarbinieku pārvaldību, kā arī piedāvā tādus pakalpojumus kā LLM modeļu apmācība un precizēšana, MI aģenti un asistenti, MLOps un MI infrastruktūra. Uzņēmums atbalsta arī individuālo karjeras attīstību, īstenojot mentoringa un izglītības programmas, kas aptver sagatavotību karjerai, gatavošanos darba intervijām un orientēšanos starptautiskajā darba tirgū. Tā darbība apvieno praktisku inženierijas un personāla atlases pieredzi, lai palīdzētu klientiem izveidot tehniskās komandas un izmantot MI uzņēmējdarbības vajadzībām.
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Vakances uzņēmumā

Staff Research Engineer, AI and Machine Learning — India Remote

Lead frontier AI research at Gramian Consulting by designing experiments, prototypes, and evaluation systems. This contract role focuses on advancing machine learning methods and translating research into practical technical outcomes.

IDIndonēzijaINIndijaKEKenijaNGNigērijaPKPakistānaTRTurcijaAttālinātiLīgumsVadošais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta pētnieksMašīnmācīšanās inženieris
Python

Apraksts

  • Study the capabilities, limitations, and training approaches of frontier AI systems.
  • Define research questions that guide AI products, platforms, and technical direction.
  • Investigate synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation methods.
  • Track advances in machine learning and identify opportunities for substantive technical contributions.
  • Build research-quality datasets, experiments, prototypes, tools, and evaluation frameworks.
  • Train, test, and assess models with current AI and machine learning technologies.
  • Interpret experimental results and draw conclusions supported by evidence.
  • Implement disciplined practices for data quality, reproducibility, experimental design, and evaluation.
  • Refine research hypotheses into validated technical insights through iteration.
  • Partner with Research, Engineering, Product, and Operations teams to apply findings to real-world use cases.
  • Present technical results clearly to specialist and cross-functional audiences.
  • Support technical reports, publications, open-source work, workshops, or conferences when relevant.
  • Mentor engineers and researchers while participating in technical reviews and discussions.

Prasības

  • A Ph.D. or master’s degree in artificial intelligence, machine learning, computer science, or a closely related technical discipline.
  • At least 7 years of professional experience, including substantial research engineering work in machine learning or frontier AI systems.
  • Strong machine learning fundamentals and practical experience designing experiments, training and evaluating models, or building AI systems.
  • Research experience in synthetic or agentic data generation, reinforcement learning or post-training, model understanding, AI evaluation, benchmarks, or agent and tool-use systems.
  • Advanced Python skills for rapidly implementing, testing, and refining research ideas.
  • Hands-on familiarity with contemporary AI and machine learning frameworks, tools, and research workflows.
  • Sound scientific judgment regarding experimental rigor, data quality, reproducibility, and evidence-based decisions.
  • Excellent technical communication skills and the ability to work independently across research and engineering teams.

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