Top Machine Learning Jobs in Atlanta, GA

Own clinical quality for member-facing AI products by partnering with product, engineering, and clinical teams. Design clinical AI evaluations, define quality thresholds and rubrics, assess accuracy, omissions, hallucinations, medication-safety risks, and translate clinical reasoning into prompts and decision logic. Monitor evolving evidence and standards of care, validate product launches, and communicate findings to technical and clinical audiences.

Manage post-sales relationships with a portfolio of customers, primarily financial institutions, to drive adoption and business outcomes from BioCatch’s behavioral biometric solution. Responsibilities include strategic consulting, project coordination, risk and escalation management, customer presentations, quarterly business reviews, roadmap feedback, stakeholder communication, team coaching, statements of work, and identifying expansion opportunities with account managers.

Lead design and implementation of Headway's insurance systems (eligibility, pricing, matching, claims). Build data-intensive, ML-powered platforms and automation, mentor engineers, write high-impact code, and improve accuracy and reliability across state and payer complexity to scale insurance-covered therapy.

Leads business analysis, advanced analytics, KPI development, data modeling, reporting automation, and AI/ML initiatives supporting global data-center construction and operational excellence. Builds datasets, dashboards, performance metrics, forecasts, and scenario models; translates complex findings for executives; aligns technology solutions with business needs; and promotes data governance, documentation, process improvement, and analytics maturity across cross-functional teams.

Design and deploy production recommendation and retrieval engines, build data orchestration pipelines for multiple modalities, implement agentic workflow frameworks, and prototype, optimize, and scale models with monitoring, governance, and low-latency SLAs.

Owns the roadmap, problem definition, business cases, prioritization, and delivery for a core fintech platform area. Partners with product owners, engineering, data science, marketing, sales, clients, and support to develop scalable, data- and AI-driven capabilities. Monitors adoption, time-to-value, and retention, supports go-to-market activities, incorporates customer feedback, and addresses regulatory and compliance requirements.

Design, deploy, and manage machine learning models supporting client acquisition, retention, and reactivation. Develop Next Best Action, CRM, paid media, and personalization solutions using LLMs and traditional ML. Design and interpret experiments, analyze large-scale datasets, communicate recommendations to stakeholders, and collaborate with product, design, and engineering teams on product and infrastructure roadmaps.

Designs, develops, deploys, evaluates, secures, and maintains enterprise AI, machine learning, generative AI, and LLM solutions for government applications. Responsibilities include data preparation, model training and monitoring, evaluation, red-team testing, safety controls, documentation, governance, privacy protection, cybersecurity compliance, architecture reviews, and stakeholder collaboration. The role translates mission and technical requirements into production-ready, responsible AI capabilities.

Designs and develops content governance platforms, anti-abuse tools, rule engines, and scalable governance pipelines. Integrates recommendation systems, implements content takedown policies, and builds capabilities for content review, risk detection, policy enforcement, and effectiveness analysis. The role addresses spam, fraud, traffic diversion, low-quality content, and black- or gray-market activity while collaborating with product, operations, algorithm, and business teams.

Founding Engineer responsible for building FilmoreAI’s production AI and data platform for construction equipment dealers. The role covers agent infrastructure, model routing, LLM extraction and reasoning, canonical data modeling, entity resolution, Python data pipelines, Azure cloud orchestration, evaluation, observability, and safe human-approved write-back. The engineer will work independently in an ambiguous startup environment and use agentic development tools to ship reliable systems with strong cost, latency, accuracy, and operational guardrails.

Design, productionize, and scale machine learning and optimization models, pipelines, libraries, and deployment platforms. Partner with data scientists, engineers, product managers, and business stakeholders to deliver ML capabilities, personalization systems, and reusable end-to-end workflows. Establish ML engineering best practices, troubleshoot data pipelines, mentor junior professionals, and help define BetterHelp’s ML platform strategy.

Design, train, and deploy scalable ML models (generative, classification, regression). Define feature roadmaps, collaborate with engineering to implement code and APIs, adapt ML methods for distributed/GPU environments, and create evaluation/annotation programs for fine-tuning and performance measurement.

Manage enterprise metadata, business glossaries, data catalogs, and end-to-end data lineage for a federal case management modernization program. Configure governance and metadata platforms, integrate data sources and pipelines, establish standards and workflows, monitor metadata quality, support compliant data sharing, develop governance metrics, document procedures, and train data stewards and business users.

Own customer outcomes from discovery through production deployment. Build decision systems using ontologies, reasoning, graph analytics, optimization, and machine learning over enterprise data. Write Python, SQL, and PyRel; debug unfamiliar systems; tune performance; harden deployments; document reusable solutions; and upstream platform improvements. Lead technical workshops and proofs of concept while partnering closely with customers, Product, and Engineering.

Drive new-logo sales and revenue growth for Wonderlic’s talent assessment and employee development solutions. Identify and prospect target clients, build relationships with HR and recruiting decision-makers, manage opportunities through the full sales cycle, close new business, and transition customers to Customer Success. Maintain expertise in products, market trends, and competitive conditions while providing strategic insights. The role requires B2B SaaS and HR technology sales experience, quota achievement, pipeline generation, and experience selling to SMB, mid-market, and enterprise buyers.

Instructor-led AI and machine learning training covering theory, data preprocessing, algorithms, model building, analytics, real-time projects, case studies, and practical business and IT applications. Participants use Python, TensorFlow, and Scikit-learn and receive certification upon successful completion.

Create end-to-end computer-use tasks for AI agents in Linux desktop environments. Design realistic multi-application scenarios, prepare files and instructions, write Python setup and automated scoring scripts, test tasks, and document them. The contract requires daily check-ins, rapid feedback, and availability throughout a three- to four-week engagement. Experience with AI tools, AI/ML projects, Linux VMs, Git, reinforcement learning environments, or computer-use benchmarks is relevant.

Own strategic partnerships with CPG customers, driving measurable outcomes, platform adoption, user expansion, and retention. Analyze usage data and business context to identify risks and opportunities, develop success plans, lead executive and operational relationships, and advocate for customers internally. Collaborate with product, sales, marketing, and support teams while contributing to repeatable playbooks, thought leadership, and customer best practices.

Build and maintain Quora’s machine learning platform and distributed model-serving infrastructure. Develop scalable systems for recommendation and language models, optimize GPU serving latency, throughput, and cost, improve ML tooling and feature stores, and contribute to platform modernization. The role includes production deployment, collaboration with senior engineers, mentoring, and participation in an on-call rotation.

Conduct applied research on scalable optimization and resource-allocation algorithms for large communication networks. Apply machine learning, reinforcement learning, integer optimization, graph-based methods, and metaheuristics to improve solution quality and efficiency. Collaborate with software engineers to integrate algorithms into production aerospace networking systems, evaluate performance at realistic scale, publish research, support patent applications, and document novel methods.

Build and maintain computer vision and machine learning pipelines for automated device inspection, grading, and quality assessment. Responsibilities include data preparation, feature engineering, model training and evaluation, production Python development, monitoring, annotation workflows, documentation, code reviews, and collaboration with product and operations teams. The role supports the full ML lifecycle and offers increasing ownership under senior engineering guidance.

Manage the operational integrity of an automated group health insurance underwriting workflow. Review and approve RFPs, validate broker and external data, correct errors, monitor funnel and risk metrics, analyze quote-to-bind performance, triage inquiries, coordinate with sales and health plan operations, and maintain underwriting dashboards and reporting.

Lead AI agent optimization efforts by designing systems that improve token efficiency, response time, reliability, and output quality. Build agentic coding systems, develop AI application patterns, own features end to end, collaborate with engineering and field teams, support the developer community, and create public technical documentation. Work across Python, TypeScript, Java, and Go while serving as a domain expert in agent design and optimization.

Design and productionize machine learning, deep learning, LLM, personalization, recommendation, search, and retrieval systems. Collaborate with product, engineering, and analytics teams to deploy AI solutions that improve customer experiences, business growth, and operational efficiency. The role requires driving projects from ideation through deployment and delivering measurable business impact in a fast-moving fintech environment.

Build and maintain high-performance, reliable backend systems for Yahoo Mail AntiSpam and Delivery. Design and develop complex server applications on Unix, leverage cloud platforms (GCP/AWS), containerization (Docker/Kubernetes), and ML/AI models to detect and deliver messages. Troubleshoot, optimize performance, and collaborate cross-functionally to ensure scalability and uptime.