Machine Learning Engineer (Hybrid)
- Model Training, and Evaluation: This encompasses the complete cycle of training, fine-tuning, and validating language models. You will be designing and adapting LLMs for use in virtual assistants, automated chatbots, content recommendation systems, etc. You will come up with evaluations for the solutions and iterate on improvements.
- Algorithm Development for Enhanced Language Understanding: Focusing on the development or refinement of algorithms to improve the efficiency and accuracy of language models and understanding and generation tasks.
- Experimentation with Emerging Technologies and Methods: Actively exploring new technologies and methodologies in language model development, including experimental frameworks and software tools.
- Education & Experience: BA/BS with 3+ years or MS in machine learning, proven project portfolio.
- ML Systems & Algorithms: Strong background in ML engineering, deep learning, and statistical modeling; experience building scalable ML solutions.
- LLM Expertise: In-depth knowledge of Transformer-based architectures (e.g., GPT) and training/fine-tuning large-scale models; exposure to Agentic frameworks.
- NLP Skills: Data preprocessing (tokenization, stemming, lemmatization), handling ambiguity and context, and transfer learning for domain/language adaptation.
- Data & Evaluation: Skilled in data annotation strategies and model evaluation with appropriate metrics (LLM as judges, RAG and Agent evaluations and so on).
- Scalability & Deployment: Experience deploying LLMs to production with efficiency, reliability, and scalability.
- Applications: Applied LLMs in chatbots, content generation, semantic search, and related use cases.
- Degree in Computer Science, Data Science, Statistics, Computational Linguistics or a related field.
- Proficiency in programming languages such as Python or R, and experience with machine learning libraries (e.g., TensorFlow, PyTorch)
- Excellent problem-solving and communication skills, with the ability to explain sophisticated concepts to non-technical partners
- Proven experience to work collaboratively in multi-functio
- 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees
- 1 paid day off for employee’s birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco
- Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees
- Exempt employees participate in Cisco’s flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)
- 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours of unused sick time carried forward from one calendar year to the next
- Additional paid time away may be requested to deal with critical or emergency issues for family members
- Optional 10 paid days per full calendar year to volunteer
- .75% of incentive target for each 1% of revenue attainment up to 50% of quota;
- 1.5% of incentive target for each 1% of attainment between 50% and 75%;
- 1% of incentive target for each 1% of attainment between 75% and 100%; and
- Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.
- For quota-based sales roles on Cisco’s sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.
- Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.
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