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# Principal Backend Software Engineer

- **Company:** Nyla Technology Solutions
- **Location:** United States
- **Salary:** $209,000 - $247,000
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Artificial Neural Networks, Microsoft Azure, Cloud Computing, Computational Linguistics, Data Security, Software Debugging, Distributed Computing Environment, Python (Programming Language), Machine Learning, Natural Language Processing, Named Entity Recognition, Performance Tuning, Tensorflow, Perplexity AI, Search Technologies, Secure Coding, Software Engineering, SQL Databases, BLEU Score, TorchServe, Pinecone, Data Processing, Qdrant, Cloud Platform System, Pytorch, Transfer Learning, Large Language Models, Prompt Engineering, Apache Spark, Deep Learning, Model Validation, Generative AI, Indexer, Backend, Fastapi, Kubernetes, Information Technology, HuggingFace, Dask, Milvus, Machine Learning Operations, Feature Extraction, Spacy, OpenSearch, Vectorization, Docker
- **Published:** November 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=eeee5f1ab01368d0

## About the Role

Advanced NLP & Deep Learning Frameworks: Hands-on expertise building and fine-tuning neural network architectures using Python and modern ML/NLP frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers, spaCy).

Production Machine Learning & MLOps: Proven track record deploying models into scalable production pipelines utilizing containerization (Docker, Kubernetes) and model-serving frameworks (e.g., Triton, TorchServe, FastAPI).

Data Manipulation & Querying: Advanced proficiency in Python and SQL for vectorization, feature extraction, and manipulation of massive structured and unstructured text datasets.

Model Evaluation & Performance Benchmarking: Expertise in implementing rigorous quantitative evaluation metrics (e.g., BLEU, ROUGE, F1-score, perplexity) and debugging complex model edge cases.

Applied Computational Linguistics: In-depth understanding of linguistic foundations, semantic analysis, named entity recognition (NER), relation extraction, and embedding techniques.

Education: Bachelor's Degree in Data Science, Computer Science, Computational Linguistics, Mathematics, or a related technical discipline, PLUS 14+ years of professional experience in data science, NLP, or software engineering OR High School Diploma / GED, PLUS 18+ years of specialized technical experience in lieu of a degree.
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Desired Skills

Large Language Model (LLM) Adaptation: Practical experience with parameter-efficient fine-tuning (PEFT/LoRA), retrieval-augmented generation (RAG) frameworks, and prompt engineering.

Distributed Data Processing: Experience leveraging distributed compute platforms (e.g., Apache Spark, Ray, Dask) to process large-scale text corpora.

Vector Databases & Semantic Search: Hands-on implementation of vector indexing and similarity search engines (e.g., Milvus, Qdrant, Pinecone, OpenSearch).

Cloud Infrastructure: Familiarity with deploying and monitoring AI/ML workloads across cloud environments (AWS, GCP, or Azure).

Secure Coding & Model Governance: Experience implementing model governance, data security, and mitigation techniques for model bias, hallucinations, and adversarial prompt attacks.

## Description

The Natural Language Processing (NLP) & Data Scientist leads the design, development, and deployment of advanced machine learning models and computational linguistics pipelines. This role is responsible for transforming massive, unstructured text and multimodal datasets into structured intelligence, developing production-grade inference pipelines, and collaborating with cross-functional engineering teams to integrate state-of-the-art models into enterprise operational environments.