2

Remote Subsea Engineering Jobs in Ohio (NOW HIRING)

Remote Subsea Engineering information

What are some common challenges faced by remote subsea engineers and how can they be addressed?

Remote subsea engineers often contend with communication barriers due to time zone differences and the need to coordinate with offshore teams. In addition, they must rely heavily on digital tools and remote monitoring systems to assess underwater equipment, which can be challenging if there are connectivity issues or data delays. To overcome these challenges, effective use of collaboration platforms, regular virtual check-ins, and thorough documentation of work are essential. Building strong relationships with on-site personnel and staying updated on the latest remote sensing technologies can also greatly enhance efficiency and problem-solving in this role.

What is the difference between Remote Subsea Engineering vs Remote Offshore Drilling Engineering?

AspectRemote Subsea EngineeringRemote Offshore Drilling Engineering
CredentialsEngineering degree, subsea certificationsEngineering degree, drilling certifications
Work EnvironmentUnderwater systems, subsea equipmentOffshore rigs, drilling platforms
Industry UsageOil & gas, subsea infrastructureOil & gas, drilling operations
Common Search IntentDesigning subsea systems remotelyManaging drilling operations remotely

Remote Subsea Engineering focuses on designing, maintaining, and troubleshooting underwater systems and infrastructure, often requiring specialized subsea certifications. Remote Offshore Drilling Engineering involves overseeing drilling operations on offshore rigs, emphasizing drilling certifications and operational expertise. While both roles operate in the oil & gas industry and may involve remote work, their core responsibilities and environments differ significantly.

What are the key skills and qualifications needed to thrive as a Remote Subsea Engineer, and why are they important?

To thrive as a Remote Subsea Engineer, you need a solid background in subsea engineering or ocean engineering, typically with a bachelor's degree and experience in offshore projects. Familiarity with remote-operated vehicles (ROVs), subsea control systems, and simulation software like AutoCAD or SolidWorks is essential. Strong problem-solving skills, attention to detail, and effective communication are crucial for managing complex underwater operations and collaborating with multidisciplinary teams remotely. These competencies ensure safe, efficient, and innovative solutions for challenging subsea environments.

What is remote subsea engineering?

Remote subsea engineering involves designing, installing, maintaining, and monitoring equipment and structures located underwater, often on the seafloor, using advanced technologies operated from a remote location. Engineers in this field work with remotely operated vehicles (ROVs), sensors, and automated systems to perform tasks such as inspections, repairs, and data collection without being physically present on site. This approach increases safety, reduces operational costs, and allows access to challenging underwater environments. Remote subsea engineering is essential in industries like offshore oil and gas, renewable energy, and marine research.
What are the most commonly searched types of Subsea Engineering jobs in Ohio? The most popular types of Subsea Engineering jobs in Ohio are:
What are popular job titles related to Remote Subsea Engineering jobs in Ohio? For Remote Subsea Engineering jobs in Ohio, the most frequently searched job titles are:
Distinguished AI/ML Engineer

Distinguished AI/ML Engineer

Frontier Technology Inc.

Dayton, OH • Remote

Full-time

Posted 24 days ago


Job description

FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

FTI Defense is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator — designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights.

This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities.


  • Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle — from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
  • Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
  • Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
  • Collaborate across engineering, data, and modeling teams to unify FTI’s AI portfolio, ensuring interoperability and reuse across mission systems.
  • Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.

  • Active Secret clearance required; TS/SCI strongly preferred.
  • Bachelor’s degree in Computer Science, Engineering, or a related technical field (Master’s or Ph.D. preferred).
  • 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
  • Experience transitioning R&D systems into accredited production environments.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

#LI-MB1

#LI-Remote