System Engineer - Machine Learning Job at Synergy ECP (Columbia)

System Engineer - Machine Learning

The tasks for this position will be focused on testing the integration of GOTS/C...

Location

United States , Columbia

Salary:

180000.00 - 250000.00 USD / Year

Synergy ECP

Expiration Date

Until further notice

Requirements

Fourteen (14) years of experience as a SE in programs and contracts of similar scope, type, and complexity is required
Bachelor’s degree in System Engineering, Computer Science, Information Systems, Engineering Science, Engineering Management or related discipline from an accredited college or university is required
Five (5) years of additional SE experience may be substituted for a Bachelor’s degree
Strong interpersonal, communications and writing skills
Basic Linux skills required
TS/SCI w/ Polygraph clearance required
U.S. Citizenship required

Job Responsibility

Testing the integration of GOTS/COTS Machine Learning models into FETS current product line
Focused on quantitative and qualitative testing along with optimizing system performance
Characterization of large data sets through some level of automation

What we offer

Highly competitive compensation
Comprehensive Health Benefits package
401K Retirement plan
People Partners to help navigate personal and professional worlds
Wellness related resources
Company-sponsored continuing education program
Generous Paid Time Off
11 paid holidays a year
Flexible work options
Philanthropy program participation

Fulltime

Senior Machine Learning System Engineer

As a Senior Machine Learning System Engineer on the AI & ML Platform team, you w...

Location

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

5+ years of experience in building Machine Learning and AI infra/platform/system
Comprehensive ML lifecycle expertise: proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring
Large-scale system design: Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning
Proficiency with frameworks and languages: Good proficiency in Python and familiarity with ML frameworks like PyTorch, TensorFlow, or JAX
MLOps and automation: Some experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models

Job Responsibility

Collaborate with your teammates to solve complex problems, from technical design to launch
Deliver cutting-edge solutions that are used by other Atlassian teams and products to build AI features that reach millions of customers
Deliver code reviews, documentation & bug fixes within a strong engineering culture
Partner across engineering teams to take on company-wide initiatives spanning multiple projects
Mentor junior members of the team

What we offer

Atlassian offers a wide range of perks and benefits designed to support you, your family and to help you engage with your local community. Our offerings include health and wellbeing resources, paid volunteer days, and so much more

Principal Machine Learning System Engineer

As a Principal Machine Learning System Engineer on the AI & ML Platform team, yo...

Location

Salary:

Not provided

Atlassian

Expiration Date

Until further notice

Requirements

Extensive experience in building Machine Learning and AI infra/platform/system (generally 5+ years)
Comprehensive ML lifecycle expertise: proven experience developing, deploying, and maintaining end-to-end ML systems, from data engineering to model serving and monitoring
Large-scale system design: Extensive experience designing and building scalable, fault-tolerant, and high-performance distributed systems for machine learning
Proficiency with frameworks and languages: Expert-level proficiency in Python and ML frameworks like PyTorch, TensorFlow, or JAX. Familiarity with other languages like Go, Java, or Scala is also beneficial
MLOps and automation: Deep experience implementing MLOps, CI/CD pipelines, and automation for continuous training, deployment, and monitoring of ML models

Job Responsibility

Collaborate with your teammates to solve complex problems, from technical design to launch
Deliver cutting-edge solutions that are used by other Atlassian teams and products to build AI features that reach millions of customers
Deliver code reviews, documentation & bug fixes within a strong engineering culture
Partner across engineering teams to take on company-wide initiatives spanning multiple projects
Mentor junior members of the team

What we offer

health and wellbeing resources
paid volunteer days

Senior Machine Learning Engineer, Reinforcement Learning

About the Role: We are looking for a Senior Machine Learning Engineer with stron...

Location

United States , Beverly Hills, CA

Salary:

150000.00 - 185000.00 USD / Year

Snail Games

Expiration Date

Until further notice

Requirements

Strong foundation in machine learning, with hands-on experience building, training, and iterating on applied ML systems
Professional or substantial project experience with reinforcement learning, agent-based systems, sequential decision-making, or closely related areas
Strong Python skills and experience with modern ML frameworks such as PyTorch
Experience designing experiments, evaluating model behavior, and improving results through systematic iteration
T-shaped capability: deep machine learning expertise plus practical range across one or more adjacent areas such as simulation, evaluation, model integration, systems collaboration, or robotics-adjacent machine learning
Strong problem-solving ability, sound judgment, and comfort working in ambiguous, fast-changing environments
Respectful, low-ego collaborative style and willingness to work beyond a narrow specialty when the work requires it

Job Responsibility

Design, train, and iterate on machine learning models for intelligent agents and decision-making systems, with an emphasis on reinforcement learning and related approaches
Define and refine state representations, action spaces, reward structures, and evaluation criteria to improve agent behavior
Build and improve practical experimentation and training workflows, including data generation, experiment tracking, and reproducibility
Analyze results, debug model behavior, and make pragmatic tradeoffs between model performance, iteration speed, and system complexity
Work closely with engineers and other partners to help integrate successful ML work into usable product systems
Contribute thoughtful technical input on next-step experiments, tooling, and ML direction as Egofold continues to evolve

What we offer

True focus on work/life balance
Paid company holidays, vacation, and separate sick leave
Medical, dental, vision, and Life/LTD
401k with company match

Fulltime

New

Sr Machine Learning Engineer

Let’s do this. Let’s change the world. We are looking for a highly motivated exp...

Location

India , Hyderabad

Salary:

Not provided

Amgen

Expiration Date

Until further notice

Requirements

Hands-on experience with AWS, Databricks, Apache Spark, PySpark, SparkSQL, Python, and SQL for large-scale data engineering
Strong proficiency in workflow orchestration, Spark performance tuning, and scalable batch and streaming data pipeline development
Experience with real-time data processing and integration using Apache Kafka, Debezium, or similar streaming technologies
Hands-on experience with MLOps tools and practices, including MLflow, model serving, feature stores, experiment tracking, deployment, and lifecycle management
Experience with GenAI engineering practices, including prompt engineering, LLM evaluation, AI observability, agentic workflows, and knowledge graphs
Ability to design and develop APIs or service interfaces for data, ML, and GenAI application integration
Experience with Agile/SAFe delivery models, DevOps practices, CI/CD concepts, and cross-functional team collaboration
Strong analytical, problem-solving, debugging, communication, and teamwork skills
Ability to quickly learn, adapt, and apply emerging technologies across data, ML, and AI engineering
Doctorate degree / Master's degree / Bachelor's degree and 8 to 13 years of experience years of experience in Computer Science, IT or related field

Job Responsibility

Design, deploy, monitor, and optimize production-grade ML and Generative AI applications for AI-enabled manufacturing solutions
Define technical architecture, engineering standards, and best practices across data engineering, ML, GenAI, analytics, and platform capabilities
Partner with business stakeholders, product owners, and cross-functional teams to translate manufacturing challenges into secure, scalable, production-ready AI and data solutions
Design, develop, and maintain complex ETL/ELT pipelines in Databricks using PySpark, Scala, and SQL for large-scale structured and unstructured data processing
Build efficient ingestion, transformation, migration, and deployment pipelines across databases, APIs, logs, event streams, images, PDFs, documents, and third-party platforms
Design and implement GenAI solutions including RAG, embeddings, vector databases, agentic workflows, tool-calling systems, LLM orchestration, serving optimization, knowledge graphs, and metadata-driven retrieval
Build GenAI applications using frameworks and platforms such as LangChain, LangGraph, LlamaIndex, DSPy, OpenAI APIs, Amazon Bedrock, or equivalent technologies
Develop evaluation and observability frameworks to monitor model quality, hallucination rates, drift, retrieval effectiveness, latency, token usage, cost, reliability, operational health, and business impact
Build and maintain MLOps and LLMOps capabilities, including experiment tracking, model registry, prompt management, versioning, CI/CD, automated testing, deployment automation, monitoring, governance, and release controls
Design scalable data quality, validation, security, privacy, access control, logging, governance, and interoperability capabilities across hybrid cloud environments

Fulltime

New

Lead Machine Learning Engineer

Lead Machine Learning Engineer At Capital One, we are changing banking for good...

Location

United States , Cambridge, Massachusetts; Richmond, Virginia; McLean, Virginia

Salary:

197300.00 - 225100.00 USD / Year

Capital One

Expiration Date

Until further notice

Requirements

Bachelor’s Degree
At least 6 years of experience designing and building data-intensive solutions using distributed computing (Internship experience does not apply)
At least 4 years of experience programming with Python, Scala, or Java
At least 2 years of experience building, scaling, and optimizing ML systems

Job Responsibility

Partner with a cross-functional team of engineers, data scientists, product managers, and designers to deliver AI-powered products that change how our associates work and provide value to our customers
Design, develop, test, deploy, and support AI software components utilizing machine learning models, including model evaluation and experimentation, large language model inference, similarity search, guardrails, governance, observability and agentic AI
Fine-tune, develop and evaluate machine learning and foundation models
Collaborate as part of a cross-functional Agile team to create and enhance software that utilizes state-of-the-art AI and ML capabilities
Contribute thought leadership and technical vision to the long term roadmap of pioneering AI systems at Capital One
Leverage a broad stack of Open Source and SaaS AI technologies
Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues
Retrain, maintain, and monitor models in production
Construct optimized data pipelines to feed ML models
Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI

What we offer

Performance based incentive compensation
cash bonus(es) and/or long term incentives (LTI)
comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being

Fulltime

New

Staff Machine Learning Engineer

Applied AI is a horizontal AI team at Uber partnering with product and platform ...

Location

India , Bangalore

Salary:

Not provided

Uber

Expiration Date

Until further notice

Requirements

10+ years of industry experience in machine learning or software engineering, with a proven record of delivering ML solutions to production
Strong knowledge of machine learning, deep learning, and exposure to generative AI techniques (e.g., transformers, LLMs, diffusion)
Experience designing and scaling ML systems or platforms, including training pipelines, serving infrastructure, and model lifecycle tooling
Fluency in ML frameworks (e.g., PyTorch, TensorFlow, JAX) and development in Python and/or scalable backend languages (e.g., Java, Go)
Excellent collaboration and communication skills with the ability to work across teams and functions

Job Responsibility

Design and implement ML-driven systems that power core Uber experiences, with a focus on scalability, reliability, and performance
Lead the technical execution of key projects involving classical ML, deep learning, and generative AI technologies (e.g., LLMs, multimodal models)
Collaborate closely with product, data science, and infrastructure teams to develop AI solutions from ideation through production deployment
Contribute to and influence the technical direction for Applied AI, particularly around system design, model architecture, and infrastructure decisions
Champion engineering best practices in ML development — including experimentation workflows, model versioning, evaluation, monitoring, and responsible AI
Provide mentorship to engineers on the team and across partner orgs to help raise the technical bar

Fulltime

New

Software Machine Learning Engineer

As a Machine Learning Engineer, you will design, develop, and deploy applied AI ...

Location

United States , North Reading

Salary:

116500.00 - 186400.00 USD / Year

Teradyne

Expiration Date

Until further notice

Requirements

2+ years of experience in machine learning, applied AI, or related fields
Hands-on experience building and deploying ML models
Exposure to production ML systems (MLOps, monitoring, deployment) is desirable
Ability to work collaboratively across teams
Strong analytical and problem-solving skills
Basic understanding of software engineering practices and version control
Ability to work cross-functionally with product, software, and hardware teams
Strong communication skills
comfortable engaging directly with customers and stakeholders
Strong problem-solving and reasoning skills

Job Responsibility

Design and implement pipelines for training, evaluation, and deployment of ML models
Apply graph ML methods to model relationships in structured and unstructured data
Build and experiment with reinforcement learning algorithms (e.g., policy gradients, PPO, Q-learning) for optimization and decision-making tasks
Incorporate interpretability and explainability techniques (e.g., SHAP, LIME, attention-based methods) into ML systems
Collaborate with software, product, and application engineering teams to integrate ML solutions into production systems
Assist in defining evaluation metrics and validation strategies for ML models
Work with internal stakeholders to understand engineering workflows and translate them into ML-driven solutions
Contribute to improving ML infrastructure, tooling, and best practices

What we offer

Medical, dental, vision, Flexible Spending Accounts, retirement savings plans, life and disability insurance, paid vacation & holidays, tuition assistance programs, and more

Fulltime

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System Engineer - Machine Learning

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