Offer summary

Qualifications:

Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field., 5+ years of software engineering experience, preferably in industrial enterprise applications., 1.5+ years of experience in AI/ML engineering roles, ideally in enterprise or manufacturing-focused products., Expert-level Python skills and proficiency in PyTorch, with hands-on experience using Hugging Face tools..

Key responsabilities:

Design, develop, and deploy scalable AI models for various Solumina AI offerings.

Collaborate with cross-functional teams to implement domain-specific reasoning models for manufacturing workflows.

Own the end-to-end ML lifecycle, including data ingestion, model training, and deployment.

Mentor junior engineers and contribute to best practices in AI architecture and MLOps.

Job description

The Lead/Senior AI Engineer will play a critical role in designing, developing, and deploying AI-driven solutions as part of Solumina AI, iBase-t’s enterprise AI initiative. This position will directly contribute to the evolution of smart manufacturing systems by building advanced models that support our four core offerings: Digital SME, Solumina Intelligence, Solumina PulseAI, and Solumina ScanAI. You’ll lead technical design for production-grade, explainable, and secure AI systems using LLMs, NLP, OCR, and GenAI techniques. You will also help define the architecture for future AI capabilities, including domain-specific reasoning models and agentic workflows.

This is a hands-on, high-impact role perfect for engineers who want to shape the future of AI in mission-critical A&D environments.

- Design, develop, and deploy scalable AI models for Solumina AI offerings including knowledge retrieval, anomaly detection, document parsing, and intelligent reporting.

- Fine-tune and deploy LLMs using the Hugging Face ecosystem (Transformers, Datasets, Evaluate, Accelerate).

- Build and maintain AI pipelines leveraging Python, PyTorch, and FastAPI to enable model deployment and inference at scale.

- Collaborate with cross-functional teams to define and implement domain-specific reasoning models for manufacturing and aerospace workflows.

- Develop future-ready agentic AI workflows to support multi-step task automation and planning.

- Own the end-to-end ML lifecycle—from data ingestion and preprocessing to model training, evaluation, deployment, and monitoring.

- Design robust APIs and microservices to integrate AI into the Solumina platform and external interfaces.

- Apply best practices in responsible AI—ensuring bias mitigation, security, explainability, and traceability.

- Stay current with state-of-the-art AI research, with a focus on foundation models, reasoning agents, and GenAI applications in industrial use cases.

- Mentor junior engineers and contribute to team-wide best practices in AI architecture and MLOps.

Requirements

- Expert-level Python skills, with experience in modular, testable, production-quality code.

- 5+ years of software engineering experience (with preference in industrial enterprise application related areas such as manufacturing, aerospace & defense)

- 1.5+ years of experience in AI/ML engineering roles, ideally in enterprise or manufacturing-focused products.

- Hands-on experience with the Hugging Face tools, including Transformers, Trainer, Datasets, and model hub integration.

- Demonstrated experience developing AI-driven applications that leverage RAG, tool calling, and/or agent orchestration via frameworks like LangChain, LangFlow, or LlamaIndex and infrastructure components like Vector Databases and Document

Parsing tools.

- Proficiency in PyTorch, with working knowledge of TensorFlow, scikit-learn, Flask.

- Proven experience with LLM training, fine-tuning, and prompt engineering.

- Strong grasp of NLP fundamentals, transformer-based architectures, embeddings, and vector search.

- Experience deploying models via containerized services using tools like Docker and FastAPI.

- Familiarity with cloud ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).

- Knowledge of model monitoring, explainability (XAI), and security practices for production AI.

- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or a related field.

Nice to Have

- Experience building multi-agent systems or reasoning-based AI workflows.

- Exposure to knowledge graphs, symbolic reasoning, or hybrid (neuro-symbolic) AI models.

- Familiarity with OCR pipelines and document intelligence tools.

- Experience with vector databases like Pinecone, FAISS, or Weaviate.

- Prior experience working in aerospace & defense or manufacturing systems.

- Contributions to open-source AI/ML projects or academic publications.

Benefits

What we offer

We are committed to offering the best to our employees. We offer a comprehensive benefits package that includes:

Yearly Performance Bonuses
Referral Bonuses
Comprehensive Medical/Dental/Vision Plans
Company Paid LTD/STD
Company Paid Life Insurance
HSA/FSA
Unlimited Vacation
40 hours of sick time per year
Paid Holidays (11 per year)
WFH Equipment Stipend
Internet/WIFI stipend
401K - company match
Educational Assistance Program

Our company values work-life balance, and for this offers benefits such as Remote Work, Flexible hours, and a Wellness program.

Non-Discrimination Disclaimer:

iBase-t is committed to providing equal employment opportunities to all qualified applicants and employees. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, or any other legally protected status. Our hiring decisions are based solely on qualifications, merit, and business needs.

Visa Sponsorship Disclaimer:

At this time, iBase-t does not sponsor visas for employment. Applicants must have valid work authorization to be considered for employment.

Salary based on experience and location.

Required profile