Develop, train, evaluate, and deploy machine learning models and AI-powered applications. Responsibilities include data preprocessing, feature engineering, deep learning development, cloud-based model deployment, and collaboration with data engineers, MLOps teams, and business stakeholders. The role also requires applying strong analytical and research skills while staying current with advances in artificial intelligence.
This is a remote position.
We’re at the cutting edge of artificial intelligence, building intelligent solutions that transform data into actionable insights. By leveraging advanced machine learning algorithms, deep learning frameworks, and scalable architectures, we deliver AI-powered applications that drive innovation and business growth. To help us achieve this, we are seeking an experienced AI & ML Engineer. The ideal candidate will be highly skilled in developing, training, and deploying machine learning models, and will be committed to turning complex datasets into practical, real-world solutions.
Requirements
Strong experience in AI/ML model development and deployment using frameworks such as TensorFlow, PyTorch, or scikit-learn.
Proficiency in programming languages such as Python, R, or Java.
Hands-on experience with data preprocessing, feature engineering, and model evaluation techniques.
Knowledge of deep learning architectures including CNNs, RNNs, Transformers, and large language models.
Experience with cloud platforms (AWS, Azure, GCP) for training and deploying ML models.
Ability to collaborate with data engineers, MLOps engineers, and business stakeholders to deliver AI solutions.
Strong problem-solving, analytical, and research skills, with a commitment to staying updated on AI advancements.
Similar Jobs
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Lead the architecture and end-to-end development of production-grade AI/ML systems, including training, deployment, monitoring, MLOps, deep learning, NLP, ASR, and agentic AI workflows. Translate research into scalable enterprise solutions, establish engineering and governance standards, evaluate emerging tools, communicate technical tradeoffs to leadership, and mentor engineers. The role requires expertise in Python, deep learning frameworks, cloud ML platforms, ML pipelines, statistics, and production LLM or agentic systems.
Top Skills:
AsrAws SagemakerAzure MlCi/CdDistributed Data SystemsGcp Vertex AiGenerative AiLarge Language ModelsMlopsNlp/NluPythonPyTorchRetrieval-Augmented GenerationTensorFlow
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
Design and operate scalable batch and streaming data platforms supporting machine learning and generative AI. Build pipelines for structured, unstructured, OCR, document, and image data; develop RAG, semantic search, and LLM-powered solutions; and establish data quality, observability, governance, orchestration, and deployment practices. Partner with stakeholders, lead platform scalability and cost optimization, mentor engineers, and translate ambiguous needs into production-ready technical roadmaps while securely handling sensitive data.
Top Skills:
AirflowAmazon KinesisSparkAWSAzureAzure Event HubsChart.JsDatabricksDeequDelta LakeDockerGithub ActionsGCPGreat ExpectationsJavaKafkaKubernetesLlmsMlopsPlotlyPysparkPythonRagScalaSeabornSnowflakeSQLTerraform
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
Architect, build, and operate production agentic AI systems for enterprise identity security. Design multi-agent orchestration, retrieval-grounding (RAG, vector stores, hybrid search), model integration and evaluation, trust and safety guardrails, observability, and reliability. Lead technical architecture, code quality, and mentor engineers to ship scalable, production-grade AI-powered access management features.
Top Skills:
AnthropicGoogleHybrid SearchOpenaiPrompt EngineeringPythonRagRetrieval Evaluation MetricsVector Stores
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
