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Ml Inference Jobs in Baltimore, MD (NOW HIRING)

NetSage

AI Software Engineer-Principal

Annapolis, MD · On-site

$133K - $179K/yr

The ideal candidate for this position will possess deep expertise in AI/ML technologies, software ... Strong understanding of statistical modeling, probability theory, Bayesian inference, covariance ...

Deloitte

Google AI Lead Architect

Baltimore, MD

$55 - $75.25/hr

Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...

iNovex Information Systems

Data Scientist 4

Annapolis, MD · On-site

$211K - $266K/yr

Job Brief Python, Jupyter, AI/ML Are you VIGILANT about your career? RealmOne definitely is ... Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)

iNovex Information Systems

Data Scientist 2

Annapolis, MD · On-site

$122K - $168K/yr

Job Brief Data Science, AI, ML Are you VIGILANT about your career? RealmOne definitely is! RealmOne ... Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations)

Cisive

Senior Engineer, Data and AI

Annapolis, MD · On-site

$120 - $180/hr

They will need the ability to independently develop AI/ML systems and products for both internal ... causal inference) to validate models and ensure sound decision-making.MLOps/LLMOps: Experience ...

eSimplicity

Data Engineer II

Columbia, MD · On-site

$93K - $100K/yr

Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference. * Experience designing, deploying, and supporting AI/ML solutions ...

eSimplicity

Data Engineer II

Columbia, MD · On-site +1

$93K - $100K/yr

Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference. * Experience designing, deploying, and supporting AI/ML solutions ...

eSimplicity

Data Engineer II

Columbia, MD · On-site

$93K - $100K/yr

Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference. * Experience designing, deploying, and supporting AI/ML solutions ...

eSimplicity

Data Engineer II

Columbia, MD · On-site +1

$100K/mo

Experience working with distributed computing environments, GPU-accelerated workloads, or large-scale model training and inference. * Experience designing, deploying, and supporting AI/ML solutions ...

Agile Defense

Data Scientist

Fort George G Meade, MD · On-site

$100 - $130/hr

... native ML frameworks (e.g., SageMaker, MLflow). * Maintain reproducibility and interpretability of model outputs to meet mission transparency and audit requirements. * Package model inference ...

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All JobsMl Inference JobsMl Inference Jobs in Baltimore, MD

Ml Inference information

See Baltimore, MD salary details

$37.3K

$122K

$195.3K

How much do ml inference jobs pay per year?

As of Aug 15, 2026, the average yearly pay for ml inference in Baltimore, MD is $121,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,900.00 and $135,100.00 per year, depending on experience, location, and employer.

What is ML inference?

ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.

What is the difference between Ml Inference vs Data Scientist?

AspectML InferenceData Scientist
Required CredentialsKnowledge of machine learning models, programming skillsDegree in data science, statistics, or related fields
Work EnvironmentDeploying models in production, real-time data processingData analysis, model development, research
Industry UsageAI product deployment, software companiesResearch institutions, tech firms, consulting

ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.

What are some common challenges faced by ML inference engineers when deploying models to production?

ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.

What are the key skills and qualifications needed to thrive in ML inference?

To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.

Is ML inference a high paying job?

ML inference roles are generally well-paying, especially for those with skills in machine learning frameworks, programming, and cloud platforms. Salaries vary based on experience, location, and industry, but they tend to be higher than average for tech-related positions.

What are popular job titles related to Ml Inference jobs in Baltimore, MD?

For Ml Inference jobs in Baltimore, MD, the most frequently searched job titles are:

What job categories do people searching Ml Inference jobs in Baltimore, MD look for?

The top searched job categories for Ml Inference jobs in Baltimore, MD are:

What cities near Baltimore, MD are hiring for Ml Inference jobs?

Cities near Baltimore, MD with the most Ml Inference job openings:

Ml Inference jobs near you

AI Software Engineer-Principal

NetSage

Annapolis, MD • On-site

$133K - $179K/yr

Full-time

Posted 16 days ago

Job description

At NetSage, we are more than a government contractor-we are a mission-focused partner dedicated to advancing national security through exceptional cyber expertise. We believe our success begins with our people, which is why we invest in and care for our employees. We know that employee retention is mission continuity, and we are committed to building long-term careers where our people can grow alongside our customers' evolving missions. Our employees enjoy meaningful work, competitive compensation, outstanding benefits, and opportunities to expand their skills across multiple mission areas. To learn more about our comprehensive benefits and what it's like to build your career at NetSage, visit our Careers page.
Due to the sensitive nature of the work we support, some job descriptions intentionally provide a high-level overview of the role. If you'd like to learn more about a particular opportunity, we encourage you to apply directly or connect with us through our Get In Touch page. We'd be happy to discuss how your experience aligns with our mission and explore where you can make an impact.
Job Description:
We are seeking a Principal Artificial Intelligence (AI) Software Engineer to design and deliver advanced artificial intelligence and machine learning (AI/ML) solutions that enhance intelligence analysis and operational decision-making. In this role, you will lead the development and operationalization of advanced AI-enabled applications integrating machine learning, large language models (LLMs), and modern software engineering practices to automate complex workflows and deliver mission-focused capabilities. The ideal candidate for this position will possess deep expertise in AI/ML technologies, software architecture, and cloud-native application development, with a proven ability to translate emerging technologies into scalable, operational solutions. Please consider applying if you meet the following qualifications.
Required Qualifications:
  • TS/SCI with polygraph security clearance.
  • A Bachelor of Science (B.S.) degree in Computer Science or a related field and eleven (11) years of relevant experience. Also acceptable are a Doctoral degree (PH.D.) and seven (7) years, a Master of Science (M.S.) degree and nine (9) years, or an Associate of Science (A.S.) degree and thirteen (13) years of relevant experience.
  • Proficiency with object-oriented languages like Java and Python.
  • Experience designing and developing AI/ML applications using modern software engineering methodologies.
  • Experience working with LLMs and generative AI technologies.
  • Experience with modern deep learning architectures, including deep neural networks (DNNs), recurrent neural networks (RNNs), and attention-based architectures.
  • Experience with ML techniques, including classification, clustering, collaborative filtering, semantic search, and information retrieval.
  • Experience using Jupyter Notebooks.

Desired Qualifications:
  • Experience implementing retrieval-augmented generation (RAG), Model Context Protocol (MCP), and AI agent frameworks.
  • Experience designing autonomous or agentic AI systems.
  • Strong understanding of statistical modeling, probability theory, Bayesian inference, covariance analysis, and machine learning fundamentals.

Apply