Top Machine Learning Jobs in Baltimore, MD

Supports computer network operations capability development across the full project lifecycle. Leads agile teams conducting reverse engineering, vulnerability analysis, software and analytic development, malware research, cryptographic solution design, and exploit-related security work. Applies automation, virtualization, AI and machine learning, and network operations expertise to develop resilient capabilities, address system and policy constraints, and counter advanced adversaries in national security environments.

Develop and deploy AI/ML solutions for classified government and intelligence workflows. Responsibilities include building LLM-powered and agent-based automation, integrating AI into operational systems, developing data pipelines, evaluating models, optimizing workflows, and conducting operational testing. The role requires collaboration with mission users, analysts, developers, and leadership while ensuring scalable, reliable, and secure production solutions.

Designs, develops, tests, implements, and maintains Linux-based systems supporting Air Force Intelligence Operations. Responsibilities include Linux administration, security hardening, patching, troubleshooting, automation, virtualization, cloud implementation, system monitoring, and customer-focused solution development across global multi-infrastructure environments.

Own data quality across systems by designing validation rules, reconciliation processes, profiling workflows, and quality controls. Investigate discrepancies to identify root causes, apply statistical methods to detect anomalies, evaluate machine learning model outputs, and communicate findings to technical and non-technical stakeholders. Partner with engineering, BI, and business teams to establish data quality standards, metrics, controls, and reporting practices.

Lead the architecture, development, deployment, and reliability of cloud-based customer experience platforms using AWS, Genesys Cloud, and Salesforce Service Cloud. Design integrations, data pathways, CI/CD pipelines, and infrastructure automation while ensuring security, compliance, scalability, and performance. Serve as a technical subject matter expert, guide global agile teams and vendors, coach engineers, establish DevOps practices, and troubleshoot critical production issues.

Build and maintain Safari AI’s cloud infrastructure, including production services, system design, reliability, documentation, and security compliance. The role sets technical direction for the cloud stack, collaborates with engineering and operations teams, improves development processes, and delivers incremental features. Candidates should have 4–6 years of software engineering experience, public cloud expertise, and experience taking complex services from concept through production. Streaming processing and machine learning experience are advantageous.

Principal Software Engineer responsible for setting engineering standards across Shippo’s data organization. Designs and builds interfaces between application services, ML systems, and data platforms; develops scalable, secure, observable production systems; guides technical architecture through RFCs and design reviews; productionizes analytical and prototype work; advises on ML workflows and agentic AI; and mentors engineers while driving cross-team technical direction.

Leads AstraZeneca’s U.S. rare neurology sales organization across gMG, NMOSD, and emerging indications. Oversees multi-level sales leadership, national and regional execution, launches, forecasting, market access partnerships, KOL and advocacy engagement, and commercial performance. Drives AI-enabled targeting, analytics, customer engagement, and operational excellence while building a high-performing, compliant, patient-centric organization. Requires extensive specialty and rare disease pharmaceutical sales leadership, biologics commercialization, launch experience, and regular nationwide travel.

Design, develop, implement, support, and improve financial-system integrations, databases, reporting solutions, and automated processes. Lead technical financial systems projects from requirements gathering through implementation, focusing on Aderant Expert, SQL Server, SSIS, SSRS, and T-SQL. Collaborate with Finance, IS, vendors, and business stakeholders; troubleshoot complex data issues, optimize database performance, document technical solutions, and support multiple concurrent initiatives.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Own Litify’s AI Call Intelligence product line end to end, including call capture, transcription, summaries, conversational insights, voice agents, and agentic workflows. Define the roadmap, quality standards, guardrails, and evaluation practices; lead client discovery, beta programs, competitive research, backlog prioritization, and cross-functional delivery. Partner with engineering, design, data science, and go-to-market teams to launch products, drive adoption, and measure outcomes.

Serves as a trusted technical advisor to U.S. government customers, assessing data platforms and defining modernization roadmaps. Designs and implements secure architectures across data management, integration, search, analytics, and AI. Leads proof-of-concept through production delivery, including automation, APIs, pipelines, troubleshooting, documentation, and knowledge transfer. Develops and operationalizes machine learning and RAG solutions, collaborates with engineering and product teams, mentors consultants, and presents technical solutions to stakeholders.

Provides full-lifecycle systems engineering services, translating customer needs into functional and technical requirements and serving as a liaison between customers and development teams. The role requires communicating complex technical concepts, managing expectations, and collaborating within Agile environments. Desired work includes coordinating AI-driven solution design and deployment, evaluating AI approaches, and partnering with engineers and domain experts to integrate emerging technologies into existing architectures.

Drafts and prosecutes U.S. and international patent applications focused on quantum computing and emerging technologies. Responsibilities include working with inventors and engineers, preparing Office Action responses, managing patent portfolios, advising on patent strategy, and developing client relationships. Requires substantive quantum computing patent experience, USPTO registration, a technical degree, a JD, and at least three years of patent preparation and prosecution experience.

Leads Sophos’s Americas MSP channel strategy, revenue growth, partner productivity, and operating performance. Oversees recruitment, onboarding, enablement, retention, distribution relationships, recurring-revenue forecasting, strategic negotiations, and program optimization. Builds and coaches direct and matrixed teams while influencing product, pricing, investments, and partner-program decisions. Uses performance data and market intelligence to improve activation, adoption, retention, expansion, and return on investment across cybersecurity managed-service offerings.

Lead client-facing AI program governance and delivery as PMO manager. Translate business objectives into AI roadmaps and OKRs, oversee AI/ML lifecycle, ensure data readiness, model validation, deployment, and responsible AI compliance. Manage PMO standards, portfolio prioritization, AI-augmented reporting, and lead executive communications while mentoring PMs, TPMs, and analysts.

Serve as lead legal advisor to product, engineering, and technology teams on AI, software, cloud, privacy, cybersecurity, intellectual property, and technology transactions. Develop AI governance and responsible-use policies, assess regulatory and ethical risks, negotiate technology and AI vendor agreements, advise on IP and data workflows, monitor global technology regulations, and train employees. The role requires significant legal experience, active bar membership, AI and privacy expertise, and the ability to influence executive and cross-functional stakeholders.

Own and scale the company’s global privacy and data protection program. Advise product, engineering, sales, marketing, security, and executives on privacy laws, data transfers, DPAs, AI governance, security commitments, incident response, and regulatory requirements. Manage privacy assessments, data inventories, notices, training, outside counsel, and vendor relationships. Partner with Security and GRC on audits, certifications, breach response, government requests, and customer obligations while building scalable processes and eventually a privacy team.

Designs and operates production data infrastructure, ETL/ELT pipelines, APIs, containerized AWS services, and graph-based systems. Responsibilities include relational, document, and graph database architecture; data quality and lineage; CI/CD automation; and integration of blockchain, financial, and investigative data. Partners with R&D, data scientists, and investigations teams to deliver production software for federal and commercial clients.

Lead the Personal Loans portfolio strategy, quantitative analysis, risk-based pricing, deal economics, and profitability initiatives. Manage a distributed analytics and portfolio team across New York and Israel, align strategies with partners, and collaborate with Risk, Product, Capital Markets, and Engineering. Translate complex credit and financial analysis into executive recommendations while optimizing customer conversion, risk-adjusted yield, margins, and lifecycle outcomes.

Lead a portfolio of technology-enabled continuous improvement initiatives for internal operations and DoD customers. Manage product backlogs, write user stories, define roadmaps, gather requirements, and facilitate Agile, Scrum, SAFe, and PI planning activities. Drive Splunk analytics, dashboarding, alerting, AI, ML, automation, proactive monitoring, and predictive analytics solutions. Ensure stakeholder alignment, measurable operational improvements, and compliance with DoD security requirements while maintaining an active Secret clearance.

Leads data engineering and data science teams, setting strategy and delivering scalable pipelines, data architecture, models, analytics infrastructure, and data governance. Partners with product, analytics, and business stakeholders to prioritize initiatives, assess upstream changes, maintain data quality, and support Snowflake-based warehousing. This hands-on leadership role includes mentoring staff, contributing to technical codebases, and advancing data science and engineering solutions.

Develop and productionize machine learning models and predictive analytics using Python, Databricks, PySpark, SQL, and Delta Lake. Build scalable data science workflows, resolve healthcare data quality and entity-resolution issues, and apply Master Data Management practices. Partner with engineering, product, analytics, and business teams to deliver governed, HIPAA-compliant solutions. Perform exploratory analysis, feature engineering, model evaluation, deployment, documentation, and data lineage management for healthcare and member engagement initiatives.

Leads the technical architecture for Oracle Fusion Cloud ERP and SCM implementations. Owns integrations, data conversion, RICEFW design, reporting, security, environments, release strategy, testing support, and technical cutover. Oversees Oracle Integration Cloud development, FBDI and ADFdi conversion cycles, reporting solutions, code reviews, technical estimates, and onshore/offshore development teams while coordinating risks and delivery with project leadership.

Leads complex AI client projects from requirements gathering through delivery, serving as the primary client contact and coordinating Sales, Operations, Product, and Engineering. Responsibilities include defining scopes and delivery plans, managing risks, quality, timelines, budgets, profitability, and KPIs, resolving execution challenges, and improving scalable processes for AI project delivery.