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26d ago

Machine Learning Engineer

Johns Hopkins Applied Physics Laboratory (APL) Laurel, MD

Laurel, MD

26d ago

$100k - $245k/yr Full time Ai Engineer Ai Ml Artificial Intelligence

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Job Description

Join the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, MD (onsite) as a Machine Learning Engineer contributing across the full lifecycle of ML algorithm development and implementation. This role supports national defense non-kinetic systems, where you will apply modern AI methods alongside real development pipelines, simulation environments, and intelligent decision-making systems.

Compensation: $100,000 to $245,000 per year. Experience: at least 2 years. Education: Bachelor’s degree in Mathematics, Physics, Engineering, Computer Science, or a related field.

What you’ll do

Design, implement, and evaluate advanced machine learning algorithms to address real-world planning, perception, coordination, and control challenges for national defense.
Develop software pipelines that connect data streams, simulation environments, and intelligent decision-making algorithms.
Apply cutting-edge AI technologies and concepts, including deep reinforcement learning, foundation models, large language models, convolutional/recurrent/graph neural networks, computer vision, and physics-based modeling and simulation tools.
Collaborate with scientists and engineers within your group and across APL to advance solutions.
Engage with sponsors to communicate proposed concepts, solutions, and analysis.

What you bring

Bachelor’s degree in Mathematics, Physics, Engineering, Computer Science, or a related field.
At least 2+ years of experience in machine learning and data science.
At least 1 year of hands-on experience applying and/or developing ML algorithms using common libraries such as PyTorch or TensorFlow.
Strong foundational knowledge in at least two areas: classification, clustering, deep learning, reinforcement learning, computer vision (object detection and visual tracking), multi-agent systems, or optimization/control theory.
Demonstrated experience using version control software such as Git.
Strong communication skills, both verbal and written.
Ability to obtain an Interim Secret clearance by your start date and ultimately a Secret clearance. If selected, you will be subject to a government security clearance investigation and must meet eligibility requirements, including U.S. citizenship.

Technologies you’ll work with

PyTorch, TensorFlow, Git
Deep reinforcement learning, foundation models, large language models
Convolutional neural networks, recurrent neural networks, graph neural networks
Computer vision
Physics-based modeling and simulation tools

Nice to have

MS in Mathematics, Physics, Engineering, Computer Science, or a related field.
5+ years of experience designing and implementing AI/ML algorithms for a variety of datasets.
Proven experience applying state-of-the-art deep learning techniques to solve distributed resource allocation problems.
Hands-on experience building computer vision pipelines for detection, tracking, segmentation, or multi-modal sensor fusion.
Experience with modeling and simulation platforms such as AFSIM, Blender, Unity, or Unreal.
Comfort working in high performance computing environments (GPU/CPU clusters).
Proficiency in one or more: multi-agent reinforcement learning, geometric deep learning, multi-modal sensor fusion, agentic AI.
Track record of writing deployable, production-level code (Python, C/C++) for real-world applications.

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1mo ago

AI Engineer

Standard Template Labs New York, NY

New York, NY

1mo ago Closed

$160k - $230k/yr Full time Ai Engineer Ai Ml Artificial Intelligence

This position is no longer accepting applications (closed Sep 17, 2026).

Job Description

Standard Template Labs is building machine learning capabilities that act as the intelligence layer for its ITSM platform. In this role, you will research, engineer, and deploy models that support natural language understanding, knowledge extraction, workflow automation, and predictive insights derived from IT infrastructure data.

This position is based in New York, NY (onsite), with a salary range of USD 160,000 - 230,000 per year. Applicants should have a Bachelor’s or Master’s in Computer Science, AI/ML, or a related field (a PhD is a plus).

Responsibilities

Research, prototype, and productionize machine learning models for ITSM use cases including ticket triage, incident prediction, workflow recommendations, and CMDB inference.
Build scalable training and inference pipelines that integrate into the core platform.
Experiment with LLMs, embeddings, and retrieval-augmented generation (RAG) to support IT knowledge access and workflow automation.
Partner with engineers and product managers to define AI-first features that differentiate the platform.
Evaluate model performance, optimize for reliability, scalability, and cost-efficiency, and ensure AI systems operate as expected.
Stay current with advances in machine learning, LLMs, and AI infrastructure, and apply them pragmatically.

Requirements

Bachelor’s or Master’s in Computer Science, AI/ML, or a related field; PhD is a plus.
Strong software engineering fundamentals (with Python preferred) and experience using ML frameworks such as PyTorch or TensorFlow.
Experience with one or more of: NLP, LLMs, information retrieval, graph ML, or time-series forecasting.
Understanding of modern MLOps practices including model versioning, deployment, monitoring, and lifecycle management.
Comfort working in a fast-paced startup environment with end-to-end ownership.
Bonus: experience applying AI in enterprise software or ITSM contexts.

Technologies

Python
PyTorch
TensorFlow
Natural language processing (NLP)
Large language models (LLMs)
Information retrieval
Graph ML
Time-series forecasting
MLOps
Embeddings
Retrieval-augmented generation (RAG)

Benefits

Competitive compensation, equity, and benefits package.
On-site work from the Flatiron District, Manhattan office, with side-by-side time near the founding team. The team works on-site five days a week, supported by a collaborative environment and convenient public transportation access.

What We Offer

Build foundational product features for an AI-first enterprise platform.
Own critical systems that scale to millions of users.
A culture that values craftsmanship, autonomy, and technical excellence.

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1mo ago

Machine Learning Engineer

WireScreen New York, NY

New York, NY

1mo ago Closed

$150k - $195k/yr Full time Big Data Bigdata Data Architecture

This position is no longer accepting applications (closed Aug 30, 2026).

Job Description

WireScreen seeks a Machine Learning Engineer in New York, NY (hybrid) to advance entity resolution and knowledge graph development, scale data ingestion, and deploy ML models across millions of records, reporting to the VP of Engineering and collaborating with data, enrichment, and product teams.

Responsibilities

Refine current entity resolution algorithms to reveal hidden links between individuals and organizations in China
Enrich the knowledge graph by integrating alternative data sources to map power structures in China
Train, validate, and deploy ML models handling tens of millions of records daily
Collaborate with Product to define and implement evaluation frameworks for traditional ML and agent-based systems
Integrate agent workflows into internal tools to boost Research team scale and speed

Requirements

4+ years of experience tackling clustering oriented ML problems, preferably in knowledge graphs or entity resolution; other relevant domains include recommendation systems, cohort analysis, and anomaly/outlier detection
End-to-end ML model production experience, including building and operating a service from experimentation and training through testing, deployment, and ongoing maintenance; model families may include clustering, classification/regression, dimensionality reduction and embeddings, nearest-neighbor or similarity methods (e.g. KNN, SVM), ensembles, NLP, and deep learning
Strong proficiency in Python and SQL

Technologies

Python
SQL
PySpark
Temporal
FastAPI
Scikit-learn
NumPy
Docker
Terraform
Kubernetes

Benefits

Competitive compensation including salary, equity, and rapid growth potential
100% company-paid Medical, Dental, and Vision coverage for employees
FSA, HSA, and 401(k) options to help you plan for healthcare expenses and retirement
Generous paid time off plus company-wide holidays
Pre-tax commuter benefits to help you save on transit and parking
Hybrid office schedule designed to give you flexibility while staying connected with your team

NICE TO HAVE

Experience with frontier or state-of-the-art models and fine-tuning LLMs for task-specific applications
Experience handling large, heterogeneous unstructured datasets and or with semantic search, computer vision (especially OCR), or linear optimization problems
Familiarity with PySpark, Temporal, FastAPI, Scikit-learn, NumPy, Docker, Terraform, Kubernetes
Early-stage startup experience (Series B or earlier)
B2B SaaS experience
#LI-LG1

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1mo ago

Data Scientist

Leidos Bethesda, MD

Bethesda, MD

1mo ago Closed

$70k - $126k/yr Full time Analytics Artificial Intelligence Big Data

This position is no longer accepting applications (closed Aug 26, 2026).

Job Description

The Data Scientist role at Leidos focuses on research‑level data analytics, machine learning, natural language processing, and data fusion for national security. This position operates on a research‑oriented team at a customer site in Bethesda, MD, delivering results, publications, and actionable intelligence insights on site.

Job Details

Location: Bethesda, MD (onsite)
Salary: USD 69,550 – 125,725 per year
Minimum Experience: 2+ years
Education: Bachelor's degree or Master's degree (or equivalent graduate degree)

Responsibilities

Collaborate within a compact data science team and with a broader group of software developers, network engineers, senior investigators, program managers, researchers, and data analysts to design, build, and optimize a Data Science platform that produces results, disseminates findings, and supports publications and presentations.
Advance small projects that analyze diverse big data across national security, cyber security, business intelligence, online social media, human behavior, and related domains.
Support multiple concurrent projects and operate under open‑ended or high‑level guidance.
Independently and collaboratively identify discoveries with mission relevance.
Package and convey findings to non‑technical audiences in a clear, actionable manner.
Apply a blend of curiosity, quantitative acumen, and customer focus to identify novel data sources, improve predictive algorithms, and promote user adoption of advanced analytics platforms in partnership with a motivated team.
Leverage expertise in research design, exploratory analysis, quantitative methods, user interface design for applications, and customer outreach to drive impact.

Requirements

Bachelor’s degree in a quantitative or analytical field (including Computer Science, Mathematics, Economics, Statistics, Engineering, Physics, or Computational Social Science) with 2+ years of experience; or a Master’s degree or equivalent graduate degree with less than 2 years of experience.
Active TS/SCI clearance with the ability to obtain TS/SCI with polygraph.
Experience in data science, analytics, or quantitative intelligence analysis, showing progressive technical development and outcomes.
Proficiency in Python or other scripting languages.
Experience deploying data science applications (for example, using Streamlit) with Docker, Kubernetes, or OpenShift.
Familiarity with information retrieval and search technologies such as Elastic Stack (Elasticsearch and Kibana) and/or SQL.
Experience collaborating with a hybrid team of analysts, engineers, and developers to conduct research and develop deployable yet user‑friendly algorithms and analytical platforms.
Previous work in data science or research focusing on data analytics or big data that does not fit into memory.
Proven track record of active learning and creative problem solving.
Ability to analyze software development or data acquisition requirements and determine optimal, cost‑effective solutions.
Familiarity with git or other version control systems.
Demonstrated ability for independent ownership of work and timely delivery with minimal supervision.

Technologies

Python
Streamlit
Docker
Kubernetes
OpenShift
Elasticsearch
Kibana
SQL
git
neo4j
Graph ML
AWS

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