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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 (Remote Contract) | Gramian Consulting

Lead frontier AI research spanning model evaluation, experimentation, and prototype development. Gramian Consulting delivers IT professional services and engineering talent solutions.

BDBangladešaBRBrazīlijaCOKolumbijaEGĒģipteGHGanaUSAmerikas Savienotās ValstisAttālinātiLīgumsVadošais speciālistsNepieciešamā Valoda: angļuMākslīgā intelekta pētnieksMašīnmācīšanās inženieris
Python

Apraksts

  • Examine the capabilities, limitations, and training approaches of frontier AI systems
  • Define research questions that shape AI products, platforms, and technical direction
  • Investigate synthetic and agentic data generation, reinforcement learning, post-training, model understanding, benchmarks, and evaluation
  • Track machine learning advances and identify opportunities for meaningful technical contributions
  • Build research-grade datasets, experiments, prototypes, tools, and evaluation frameworks
  • Train, test, and assess models with current AI and machine learning technologies
  • Interpret experimental findings and draw evidence-based conclusions
  • Develop standards for data quality, reproducibility, experimental design, and evaluation
  • Advance research hypotheses into validated technical insights through iterative investigation
  • Partner with Research, Engineering, Product, and Operations teams to apply findings in practice
  • Present technical results 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 peer 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
  • Deep machine learning fundamentals and practical experience designing experiments, training and evaluating models, or building AI systems
  • Research experience with synthetic or agentic data generation, reinforcement learning or post-training, model understanding, AI evaluation, benchmarks, or AI agents and tool-using systems
  • Advanced Python skills for rapid implementation, testing, and iteration in research settings
  • Experience using contemporary AI and machine learning frameworks, tools, and research practices
  • 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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