2804 C Application Engineer jobs in Kearny,NJ

New, Posted 10 hours ago

Frito-Lay - Warehouser/Material Handler $18-$26/hr

Frito Lay

Newark, NJ 07104

$18-$26/hr

No Experience

Easy Apply

Quality Assurance Technician

Adecco

Parsippany, NJ 07054

$28.79/hr

~ 29 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

High School Diploma or GED required
Experience in manufacturing and/or quality inspection preferred
Ability to read and interpret technical documents and follow written and verbal instructions
Ability to lift, push, or pull up to 50 lbs and wear required PPE (safety glasses, gloves, etc.)

SmartExplore AI is experimental.

New, Posted 10 hours ago

UPS - Warehouse Worker/Package Handler $21+/hr

UPS

Belleville, NJ 07109

$21/hr

No Experience

New, Posted just now

Desktop Support Job Training Program

Year Up United Careers

Newark, NJ 07104

$525/wk

New, Posted just now

Software Engineer II

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$117,500-$157,500/yr

New, Posted 4 hours ago

Lead AI Engineer

Capital One

New York, NY 10012

Apply Directly

Desktop Support JOB Training Program

Year Up United

New York, NY 10261

$525/wk

~ 27 min Onsite

A high school graduate or GED recipient
Eligible to work in the U. S.
Have not obtained a Bachelor's degree
You may be required to answer additional screening questions when applying

SmartExplore AI is experimental.

New, Posted 1 day ago

DiversityJobs

Technical QA Analyst II

Capital Rx

New York, NY 10261

New, Posted 6 hours ago

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Principal Quant Developer (MLOps)

Fidelity Investments

Harrison, NJ 07029

~ 4 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

A Bachelor's degree in Computer Science, Financial Engineering, Information Technology, Information Systems, Mathematics, Physics, Statistics, Engineering, or a closely related field and six (6) years of experience as a Senior Quant Developer or similar role.
Alternatively, a Master's degree (or equivalent foreign education) in the same fields, accompanied by four (4) years of experience as a Lead Quantitative Development or similar role.
This experience should include building high-quality, robust, and efficient systems and solutions for financial investment decisions, utilizing R, Python, PL/SQL databases, and quantitative techniques.
Expert in Python with experience across the development stack (full stack)
Exposure to object-oriented programming (OOP) and design patterns
Experience in at least one unit testing framework and understanding of test-driven development (TDD) concepts and methodologies
A commitment to writing clean, maintainable, and efficient code, with best practices for long-term maintainability
Skilled in a range of database technologies: SQL (Oracle & Snowflake), NoSQL, Graph
Skilled in batch and API technologies: such as batch scheduling (using Autosys and Airflow) and creating REST APIs (using FAST API and Flask)
Proven ability to construct and manage robust data pipelines and event-driven workflows
Proven expertise in system design and cloud architecture on AWS, leveraging resources including Lambda, S3, EKS, and EC2
Experience in containerization with Docker and orchestration with Kubernetes
Implement CI/CD pipelines (using Linux and Jenkins), code versioning using GitHub
Experience in Infrastructure as Code methodologies for consistent and scalable infrastructure management
Experience operationalizing machine learning models on AWS, including services such as SageMaker (training, deployment, model registry, monitoring) and Bedrock (foundation model access and fine-tuning)
Operationalizing AI/ML pipelines using modern MLOps principles, including production lifecycle management of AI models
Familiarity with experiment tracking and model versioning tools (e.g., MLflow)
Identifying and deploying applied ML solutions relevant to quantitative investing: time series forecasting, anomaly detection, NLP, and predictive analytics
Awareness of responsible AI governance practices
Demonstrated enthusiasm for contributing to all facets of our AI ecosystem, from application development to MLOps/LLMOps infrastructure, with a versatile, full-stack engineering mindset
Demonstrated knowledge of mathematics, statistics, and quantitative finance
Deep understanding of quantitative techniques and methods, statistics and econometrics including probability, linear regression and time series data analysis
Analyze and design systems to implement quantitative models for systematic financial investments using R and Python, including time series forecasting models, multi-asset class portfolio construction strategies, risk management tools, alpha research, and simulation-based algorithms
Domain knowledge in either equities, fixed income or alternative asset classes
Progress towards CFA (or equivalent) a plus