Data Science ML/GenAI Engineer

What Success Looks Like

AI Use in Hiring

Role Type

Required Qualifications

• 3–5 years of experience in data science, machine learning, or ML engineering, with demonstrated experience developing production-quality code beyond notebooks.
• Master’s degree or equivalent professional experience in data science, machine learning, computer science, statistics, or a related field, with a strong foundation in statistics and modeling methodologies.
• Hands-on experience developing NLP and/or LLM-based solutions , including:
• Retrieval-Augmented Generation (RAG)
• Embeddings and similarity search, including cosine similarity
• Hybrid search combining BM25 and semantic search
• Text deduplication techniques such as fuzzy matching and MinHash
• Text classification and Named Entity Recognition (NER)
• Search re-ranking
• Prompt engineering
• Strong proficiency in Python , including experience with pandas, scikit-learn, PyTorch, and other relevant machine learning libraries.
• Strong understanding of object-oriented programming, clean code, and software design principles .
• Strong data analysis skills with experience applying statistical methods such as exploratory data analysis, hypothesis testing, and statistical modeling .
• Hands-on experience with Databricks or a comparable data/analytics platform , including the ability to independently explore, transform, and prepare data.
• Solid understanding of the machine learning lifecycle , including model training, evaluation, deployment, and production monitoring for issues such as model drift and data quality.
• Experience designing and developing REST APIs to expose data, models, or analytical results to downstream applications.
• Strong written and verbal communication skills , with the ability to collaborate effectively across technical teams with different responsibilities and priorities.

Nice-to-Have Qualifications

• Experience working with news, social media, or other large-scale unstructured text data , including media monitoring, web scraping, or APIs.
• Domain knowledge or professional experience in communications, public relations, media, or related industries .
• Familiarity with the broader LLM ecosystem , including vector databases/stores, RAG frameworks, and fine-tuning NLP models.
• Experience with MLflow or similar experiment-tracking and model-management tools .
• Basic knowledge of TypeScript and Node.js .
• Experience with CI/CD practices and version control , including Git, GitHub Actions, or equivalent tools.

Benefits

• Competitive Salary – A competitive compensation package based on experience and qualifications.
• Medical, Dental, and Vision Insurance – Comprehensive insurance coverage to support you and your family.
• 401(k) Plan with Company Match.
• Generous Paid Time Off (PTO) – Time off to support work-life balance and personal needs.
• Company-Paid Holidays – Paid holidays throughout the year.
• Flexible Work Options – Work-from-home opportunities are available, depending on role and business needs.
• On-Call Compensation – Additional pay for eligible on-call shifts.