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18d ago

Data Engineer, Lead

Booz Allen Hamilton McLean, VA

McLean, VA

18d ago

$78k - $176k/yr Full time Artificial Intelligence Data Data Architecture

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Job Description

Design and deliver enterprise data foundations that enable AI applications to use authorized information.

Responsibilities

Design enterprise data architectures and build pipelines, knowledge indexes, and retrieval services that ground agents in authorized enterprise information
Partner with source-system owners and engineering teams to define data contracts
Integrate structured and unstructured sources while maintaining permissions, lineage, quality, and freshness
Own reliability of data and retrieval services
Collaborate with AI Engineering on retrieval behavior and response quality
Support ingestion, transformation, indexing, synchronization, and retrieval service implementation and maintenance
Align engineering execution with role emphasis: architecture and governance decisions (architect) and pipeline, connector, and service implementation (engineer)

Requirements

Experience designing or implementing enterprise data platforms, lakehouse architectures, and integrations for structured and unstructured data
SQL and Python experience, including developing, testing, and operating ETL or ELT pipelines
Experience defining data models, schemas, data contracts, APIs, and access patterns for downstream applications
Experience with data governance including source permissions, lineage, quality controls, and monitoring for freshness and availability
Knowledge of retrieval-augmented generation, embeddings, vector indexes, and semantic or hybrid search
Ability to troubleshoot ingestion and retrieval failures and assess relevance, latency, scalability, and data quality
Ability to translate enterprise requirements into architecture decisions, integration standards, and governance patterns
Ability to implement and maintain ingestion, transformation, indexing, synchronization, and retrieval services
Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements
Bachelor’s degree

Technologies

SQL
Python
ETL
ELT

Nice If You Have

Experience with Databricks, Spark, Delta Lake, vector databases, or comparable platforms
Experience with permission-aware retrieval, metadata enrichment, incremental ingestion, or knowledge engineering
Experience delivering reusable customer connectors and data services for production AI applications

Benefits

Health, life, disability, financial, and retirement benefits
Paid leave
Professional development
Tuition assistance
Work-life programs
Dependent care
Recognition awards program

Vetting

Selected applicants will be subject to a government investigation
Eligibility requirements may apply for the U.S. government client

Compensation

Projected compensation range: $77,600.00 to $176,000.00 (annualized USD)

Work Model

Onsite: work will primarily be performed full-time at a customer facility in McLean, VA

Identity Statement

Applicants are expected to be on camera during interviews and assessments
Booz Allen reserves the right to take a picture to verify identity and prevent fraud

Candidate AI Usage Policy

Use of artificial intelligence (AI) or other tools to assist with responses during interviews is prohibited unless permission is explicitly provided

Commitment to Non-Discrimination

All qualified applicants will receive consideration without regard to disability, protected veteran status, or any other status protected by applicable law

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18d ago

Machine Learning Engineer

Engramme San Francisco, CA

San Francisco, CA

18d ago

Full time Python Artificial Intelligence Data Analysis

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Job Description

Engramme is seeking a Machine Learning Engineer in San Francisco, CA to build and deploy machine learning systems focused on memory retrieval and contextual understanding. The role emphasizes scalable ML infrastructure, production deployment, and real-time performance optimization.

What You Will Do

Design and implement ML models for memory retrieval and ranking
Build ML infrastructure and training pipelines
Deploy and monitor models in production at scale
Optimize model performance and latency for real-time systems
Work with vector databases and embedding systems
Apply MLOps best practices, including monitoring and operational readiness
Collaborate with the research team to productionize new algorithms

Required Qualifications

4+ years of machine learning engineering experience
Strong proficiency in Python and ML frameworks, including PyTorch and TensorFlow
Experience deploying ML models into production environments
Knowledge of MLOps, model serving, and monitoring
Understanding of NLP, embeddings, and retrieval systems
Experience with cloud platforms such as AWS and GCP, and containers
Strong software engineering fundamentals
Experience with large-scale data processing

Technologies You Will Work With

Python
PyTorch
TensorFlow
AWS
GCP
Containers
Vector databases and embedding systems

Nice to Have

Experience with large language models and prompt engineering
Knowledge of vector databases including Pinecone, Weaviate, or Milvus
Experience with recommendation systems or search
Background in information retrieval or ranking systems
Knowledge of model optimization and quantization
Experience with real-time ML systems
Familiarity with transformer architectures

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18d ago

Senior Machine Learning Engineer

GEICO Bethesda, MD

Bethesda, MD

18d ago

$153k - $300k/yr Full time Ai Ml Artificial Intelligence Automation

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Job Description

GEICO is hiring a Senior Machine Learning Engineer to help review and build machine learning solutions that address complex business needs, while also strengthening the systems that deliver those models in production. This hybrid role is based in Bethesda, MD, with responsibilities spanning deployable services/APIs, model performance monitoring, and scalable MLOps infrastructure.

You will partner with Product, Business Units, and Data Science teams to design reliable training and deployment pipelines, maintain production-grade code, and manage the full ML lifecycle. GEICO also indicates that multiple positions are open for this role.

What you’ll do

Review the architecture and implementation of machine learning models used to solve complex business problems with Product, Business Units, and Data Science teams.
Design and develop scalable infrastructure for model training, automated hyperparameter tuning, and deployment pipelines that remain reliable and performant at scale.
Write maintainable, production-grade code that converts machine learning models into deployable services and APIs.
Ensure code is modular and reusable to support future ML initiatives.
Debug model performance issues, track key metrics, and improve model reliability, speed, and efficiency in production environments.
Manage the end-to-end ML model lifecycle, including monitoring, retraining, and version management to keep models aligned with business requirements.
Promote software engineering, model development, and deployment best practices across the team.
Review technical decision-making processes and support collaboration within the team.
May require a pre-hire technical screen.

Required qualifications

Bachelor’s degree in Computer Science, Business Analytics, Machine Learning, or a related technical field.
Four (4) years of experience as a Software Engineer or related occupation.
Four (4) years of experience applying machine learning techniques, including deep learning, reinforcement learning, and NLP in production environments.
Four (4) years of experience with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
Four (4) years of experience with cloud platforms (AWS, Azure, GCP), including containerization and orchestration tools (Docker, Kubernetes) and cloud-native ML tools (AWS SageMaker, GCP AI Platform, Azure Machine Learning).
Four (4) years of experience deploying and operating machine learning models in production, including system architecture and fault-tolerant design for scalability, reliability, and high availability.
Four (4) years of experience writing production-grade, maintainable code using object-oriented design principles, including SQL, Python, and Spark for data processing that supports model development.
Four (4) years of experience with distributed systems, including distributed data processing and microservices architectures used to scale ML models in production.
Four (4) years of experience with MLOps practices, including CI, CD, automated testing, and deployment pipelines for ML models, including data/streaming pipeline tools such as Apache Kafka, Apache Flink, and Spark Streaming.
Four (4) years of experience setting up, monitoring, and logging systems to track model performance and resource utilization in production.

Technologies

TensorFlow, PyTorch, Scikit-learn
AWS, Azure, GCP
Docker, Kubernetes
AWS SageMaker, GCP AI Platform, Azure Machine Learning
SQL, Python, Spark
Apache Kafka, Apache Flink, Spark Streaming

Location and schedule

Bethesda, MD (Hybrid)
Hybrid work policy: 3 days in-office, 2 days remote; must be able to report to the local office.

Compensation

USD 152,838 - 300,000 per year.

Benefits

Competitive pay, benefits, and flexibility to support your well-being and future.
Personalized development programs, mentorship, and certification assistance.

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18d ago

Principal Machine Learning Engineer

Cushman & Wakefield Creve Coeur, MO

Creve Coeur, MO

18d ago

$179k - $210k/yr Full time Ai Ml Artificial Intelligence Azure DevOps

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Job Description

Lead the design and delivery of end-to-end AI and machine learning systems, spanning architecture, engineering, deployment, and production monitoring.

Responsibilities

Shape end-to-end architecture, development, and deployment for AI and machine learning, including GenAI and agentic models tailored to business use cases.
Design and build agentic AI systems with multi-agent orchestration, tool-use, evaluation, and autonomous task-execution pipelines for enterprise workflow automation.
Set and enforce model development standards across data preprocessing, feature engineering, model selection, hyperparameter tuning, evaluation, and documentation.
Partner with data engineering teams to deliver robust, scalable, high-quality data pipelines supporting both training and inference.
Implement MLOps and LLMOps capabilities, including CI/CD for data wrangling, feature engineering, model training, evaluation, deployment, and monitoring.
Define and enforce standards for model versioning, experiment tracking, reproducibility, and model registry management.
Build model monitoring frameworks to detect performance degradation, data drift, concept drift, and bias, including automated alerting and retraining triggers.
Implement AI governance policies for model risk management, fairness, explainability, privacy, and security.
Promote AI principles across the organization, ensuring human oversight and accountability throughout the AI development lifecycle.
Work across project and product teams and mentor engineers, while establishing ML engineering and architectural principles using Databricks on Azure.

Requirements

10+ years building software or machine learning systems, including 6+ years shipping and operating machine learning in production (served, monitored, and maintained after launch).
Experience as the senior-most or near-senior-most engineer on a production ML or data platform, owning architectural decisions that others depend on.
Proven ability to set technical standards that persist beyond your involvement and to lead through influence without formal authority.
Hands-on Python and SQL, plus software engineering fundamentals: version control, automated testing, code review, modular design, and cross-team enforcement.
Expert, hands-on Databricks proficiency (Spark, Lakeflow Declarative Pipelines, Delta Lake, Lakebase/Postgres, Unity Catalog, Model Serving) and experience with the Azure data ecosystem.
Experience with MLflow or an equivalent solution for experiment tracking, model registry, tracing, and reproducibility.
At least one year building agentic systems that reached production use (or equivalent demonstrated work).
Ability to mentor engineers at every level and raise team technical standards.
Familiarity with modern machine learning frameworks and reusable, scalable engineering patterns.

Technologies

Python, SQL
Databricks, Spark
Lakeflow Declarative Pipelines, Delta Lake, Lakebase/Postgres
Unity Catalog, Model Serving
Azure data ecosystem, CI/CD
MLflow
REST endpoints, Azure DevOps
Databricks Declarative Automation Bundles (DABs), GitHub Actions
Terraform
Model Context Protocol (MCP)

Benefits

Health, vision, and dental insurance
Flexible spending accounts
Health savings accounts
Retirement savings plans
Life and disability insurance programs
Paid and unpaid time away from work
Competitive pay (varies by eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements)
The company will not pay less than minimum wage for this role

Preferred Skills, Knowledge & Experience

Experience establishing an ML or AI platform capability in an organization without prior capability.
Experience embedding across multiple teams, geographies, and time zones as a principal-level technical contributor.
Familiarity with CI/CD and infrastructure-as-code tooling for data pipelines using Azure DevOps, Databricks Declarative Automation Bundles (DABs), GitHub Actions, Terraform, or equivalent.
Good understanding of data governance, metadata management, and cataloguing in enterprise environments.
Exposure to model serving and inference at scale (containers, REST endpoints, latency and throughput targets) or feature stores, retrieval pipelines, or LLM cost-attribution tooling.
Model Context Protocol (MCP) or comparable tool-integration standards.
Domain experience in commercial real estate, professional services, or similar environments where data is messy, entities are inconsistently defined, and subject matter experts are the source of truth.

Location: Creve Coeur, MO (onsite) | Salary: USD 178,500 - 210,000 per yearly

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18d ago

Senior Machine Learning Engineer, Perception

PlusAI Santa Clara, CA

Santa Clara, CA

18d ago

$150k - $200k/yr Full time Artificial Intelligence Engineer Engineering

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Job Description

PlusAI is building advanced perception capabilities for autonomous driving and 3D scene understanding. This onsite role in Santa Clara, CA focuses on developing Bird’s Eye View (BEV) fusion models that combine multimodal sensors, especially LiDAR. You will work on scalable perception algorithms with a clear emphasis on real-world performance, robustness, and production readiness.

Responsibilities

Design, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs.
Benchmark perception models using large-scale datasets and quantitative metrics.
Partner with teams across research, data, and deployment to refine models and enable real-world applications.
Drive a strong focus on performance, robustness, and scalability for production systems.
Perform work in accordance with the company’s Quality Management System (QMS) requirements.
Support continuous improvement by ensuring team QMS compliance, monitoring quality, and driving process improvements.

Requirements

Ph.D. or Masters in AI, Computer Science, Electrical Engineering, Robotics, or a related field.
Ph.D. new grad or Masters + 3 years of industry experience.
Proficiency in Python and experience building deep learning pipelines.
Strong experience with PyTorch, TensorFlow, or JAX.
Proven background in LiDAR-based 3D perception and BEV representation models.
Deep understanding of multimodal sensor fusion architectures and techniques.
Familiarity with camera, LiDAR, and radar modalities, including synchronization, calibration, and integration in perception pipelines.
Solid foundation in computer vision, deep learning, and 3D geometry.

Preferred Skills

Industry or academic experience in autonomous vehicle perception, robotics, or related areas.
Hands-on experience building deep learning models in real-world or production environments.
Experience with distributed training, high-performance computing, or GPU acceleration.

Compensation and Tech Stack

Salary range: USD 150,000 - 200,000 per year. Technologies include Python, PyTorch, TensorFlow, and JAX.

Benefits

Work, learn, and grow in a future-oriented, innovative, and dynamic field.
Wide range of opportunities for personal and professional development.
Catered free lunch, unlimited snacks, and beverages.
Highly competitive salary and benefits package, including a 401(k) plan.

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18d ago

Senior Machine Learning Engineer, Perception and Controls

Capstan Medical, Inc. West Menlo Park, CA

West Menlo Park, CA

18d ago

Full time Artificial Intelligence Computer Vision Data Analysis

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Job Description

Capstan Medical is hiring a Senior Machine Learning Engineer to advance perception and controls for a heart valve robotic system with real-time, FDA design-controls documentation.

Responsibilities

Develop registration methods to align intraprocedural imaging (fluoroscopy and echocardiography) to the robot.
Estimate the pose of catheters and implants from medical images.
Fuse image-based estimates with robot kinematics and additional sensing.
Quantify uncertainty for each estimate.
Build data pipelines for imaging and robot data, including capture, alignment, labeling, and dataset versioning for training and evaluation.
Use simulation and synthetic data when clinical data is limited.
Fit and improve models of device behavior from data, partnering with controls engineers to improve control performance.
Work with clinical engineers and physicians to understand what images show, what matters in the procedure, and what accuracy is sufficient.
Read relevant literature, prototype promising approaches, and report plainly what works and what does not on the team’s data.
Deploy models to the robot while meeting real-time latency budgets.
Write validation materials, test datasets, and design documentation needed for learned components to pass FDA design controls.

Requirements

Education: MS in Computer Science, Electrical Engineering, Robotics, or a related field (PhD a plus).
Experience: 4+ years of professional experience in computer vision or machine learning (classical or learned), including at least one production system shipped on real-world data.
Experience working with scarce, noisy, or expensive data, using approaches such as synthetic data, augmentation, self-supervision, or physics priors.
Experience building ML systems on data from physical systems such as robots, cameras, medical imaging, or sensors.
Ability to thrive in a fast-paced environment and own problems end-to-end.
Ability to work onsite 3–4 days per week, flexibly split between Santa Cruz, CA and West Menlo Park, CA offices, with at least 1 day per week in Santa Cruz.

Technologies

Python, PyTorch, C++
ROS, ROS2
ONNX, TensorRT
Kalman filters, factor graphs

Preferred Qualifications

Ultrasound or echocardiography experience (strongly preferred). Fluoroscopy or X-ray experience is also valuable, including 2D/3D registration or digitally reconstructed radiographs.
Experience tracking catheters, needles, surgical tools, or continuum robots in images.
Sensor fusion and state estimation experience (e.g., Kalman filters or factor graphs).
System identification or learned dynamics for control, including residual models on top of physics.
Robotics software experience with ROS/ROS2 and on-device inference under latency constraints (ONNX, TensorRT).
Data platform and MLOps experience, including dataset versioning and experiment tracking.
Medical device or safety-critical background, including validating ML under FDA design controls.
Experience as an early ML engineer on a team, setting up tools, data practices, and evaluation others build on.
Publications at venues such as MICCAI, IPCAI, CVPR, ICRA, or IROS.

Workplace

Type: Hybrid
Onsite: 3–4 days per week across Santa Cruz and West Menlo Park, CA
Requirement: at least 1 day per week in Santa Cruz

Reports to

Robotics & Controls Manager

Benefits

Outstanding benefits with medical, dental, and vision covered at 100% for you and your family, plus flex time off.
Fun, fast-paced, collaborative environment working on transformational technologies in the cardiac healthcare space.
Work-hard, play-hard environment with office outings.

AI Tools Notice

Capstan Medical may use artificial intelligence (AI) tools during parts of the hiring process (e.g., reviewing applications, analyzing resumes, assessing responses, and identifying potential inconsistencies or verification signals).
AI tools support the recruitment team but do not replace human judgment.
Final hiring decisions are made by humans.

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18d ago

Sr Machine Learning Engineer- Maps Optimization

Uber Sunnyvale, CA

Sunnyvale, CA

18d ago

$202k - $224k/yr Full time Ai Ml Artificial Intelligence Big Data

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Job Description

Join Uber’s Maps Optimization team and help power map features that impact millions of trips worldwide. In this Sr Machine Learning Engineer role, you’ll build and improve large-scale machine learning systems and models that support location search, ETA calculation, and routing, with a focus on high-throughput, low-latency predictions delivered through production APIs.

This hybrid role is based in Sunnyvale, CA and supports collaboration in-office, with employees required to spend at least 50% of their time in-office unless full remote work is approved.

What you’ll do

Develop and deploy end-to-end machine learning models and the infrastructure needed to optimize Uber map-related applications
Design and maintain high-throughput, low-latency prediction systems and APIs that handle extremely high request volumes (hundreds of billions of daily requests)
Apply optimization thinking to explore new approaches that improve logistical efficiency across Uber’s product verticals
Partner across teams with product managers, scientists, designers, and engineers to deliver holistic solutions to real-world problems

What you bring

5+ years of machine learning experience, or 2+ years if you have a PhD
2+ years in one or more areas such as machine learning, artificial intelligence, optimization, signal processing, operational research, or related technical fields
Experience building, debugging, and scaling distributed data processing and ML pipelines (examples include Apache Spark, Hive, Presto, and Michelangelo)
Knowledge of development and debugging in Java, Scala, or Golang, plus scripting experience with Python and/or shell scripts
Technical leadership experience, including working with teams, owning projects, and setting technical direction
Bachelor’s degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience

Tools you’ll use

Apache Spark, Hive, Presto, Michelangelo
Java, Scala, Golang
Python, shell scripts

Compensation and benefits

Base salary range: USD 202,000 to 224,000 per year.

Eligible to participate in Uber’s bonus program
May be offered an equity award and other types of compensation
Eligible to participate in a 401(k) plan
Eligible for various benefits

Preferred qualifications

Experience architecting large-scale, production software applications
Experience productionizing applied machine learning solutions (for example: graph or graphless prediction, learning to rank) to solve complex ML challenges
Master’s degree or PhD in Computer Science or a related technical field

Uber’s offices remain key to collaboration and culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Ask your recruiter for details about this role’s specific requirements.