Nonetype Object Is Not Subscriptable Python Jobs in Usa
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Sr. Data Engineer (PySpark & Python + AI Tools Exp.) - (Only W2 or 1099)
Charlotte, NC (Hybrid)
12+ Months Contract
Job Description:
We are currently seeking a Senior Data Engineer with hands-on coding experience and a strong background in Python, PySpark, and Object-oriented programming.
The ideal candidate will be responsible for designing, developing, and implementing new features to our existing framework using PySpark and Python.
This position requires a deep understanding of data transformation and the ability to create standalone scripts based on given business logic. Also, exposure to AI Tools and building any AI applications will be advantage.
Key Responsibilities:
- Design, develop, and optimize large-scale data pipelines using PySpark and Python.
- Implement and adhere to best practices in object-oriented programming to build reusable, maintainable code.
- Write advanced SQL queries for data extraction, transformation, and loading (ETL).
- Collaborate closely with data scientists, analysts, and stakeholders to gather requirements and translate them into technical solutions.
- Troubleshoot data-related issues and resolve them in a timely and accurate manner.
- Leverage AWS cloud services (e.g., S3, EMR, Lambda, Glue) to build and manage cloud-native data workflows (preferred).
- Participate in code reviews, data quality checks, and performance tuning of data jobs.
Required Skills & Qualifications:
- 6+ years of relevant experience in a data engineering or backend development role.
- Strong hands-on experience with PySpark and Python, especially in designing and implementing scalable data transformations.
- Solid understanding of Object-Oriented Programming (OOP) principles and design patterns.
- Proficient in SQL, with the ability to write complex queries and optimize performance.
- Strong problem-solving skills and the ability to troubleshoot complex data issues independently.
- Excellent communication and collaboration skills.
- Hands-on experience with AI Tools.
Preferred Qualifications (Nice to Have):
- Experience working with AWS cloud ecosystem (S3, Glue, EMR, Redshift, Lambda, etc.).
- Exposure to data warehousing concepts, distributed computing, and performance tuning.
- Familiarity with version control systems (e.g., Git), CI/CD pipelines, and Agile methodologies.
- Exposure to AI Tools and hands-on experience of building any AI applications.
Job Title: Senior Automation Engineer
Location: Hillsboro, Oregon
Job Type: Full-Time
Job Description:
We are seeking a highly experienced Senior Automation Engineer to join our advanced software and embedded systems team. The ideal candidate will have deep expertise in Python automation (Pytest), Robot Framework, and QNX environments, with strong skills in UX/UI automation and testing. This role involves enhancing and migrating automation frameworks, debugging complex integrations, and working closely with cross-functional teams to deliver high-quality test automation solutions for embedded systems and entertainment platforms.
Key Responsibilities
Automation Framework Development
- Architect, develop, and maintain automation frameworks primarily using Python and Pytest.
- Lead migration of existing Robot Framework tests to Python/Pytest equivalents.
- Build reusable fixtures, utilities, wrapper layers, and automation components to support large test suites.
Test Execution & Optimization
- Analyze and interpret Robot Framework keyword libraries; enable efficient reuse within Python-based executions.
- Optimize hybrid execution flows involving both Pytest and Robot Framework assets.
- Execute and maintain UI and device automation tests using tools such as Appium, Selenium, or equivalent frameworks.
Cross-Layer Debugging & Integration
- Independently debug cross-layer automation issues involving Python, Robot Framework, device tools, and operating systems.
- Integrate automation frameworks with CI/CD pipelines and tools (e.g., Jenkins, GitLab, Azure DevOps).
Collaboration & Mentorship
- Mentor and guide junior automation engineers, establishing good coding practices, test design patterns, and quality standards.
- Work collaboratively with software engineers, product developers, and QA teams to enhance automation coverage and reliability.
System & Environment Interaction
- Work with QNX OS, virtualization systems (Hypervisor), and cloud environments (AWS).
- Engage with hardware interfacing (USB, Ethernet, multimedia interfaces) and hardware simulation/ fault-injection where applicable (nice-to-have).
Required Skills & Experience
- 7–10 years experience in automation engineering with 5+ years hands-on Python automation using Pytest.
- Practical experience with Robot Framework including keywords, variables, resources, and large keyword repositories.
- Strong skills in UI automation using tools such as Appium/Selenium.
- Solid understanding of modular test design and maintainable patterns (page-object, keyword patterns).
- Experience with QNX (Posix) operating system, virtualization (e.g., Hypervisor), and cloud-based environments (preferably AWS).
- Good understanding of Git, branching strategies, and CI/CD workflows.
- Proven ability to debug complex, multi-layered test automation environments.
Preferred Qualifications
- Exposure to embedded systems, aviation, or high-volume regression environments.
- Experience in framework migration, cross-framework interoperability, or keyword reuse models.
- Background in hardware interactions and media/UX systems (multimedia I/O, touch interactions).
- Familiarity with fault injection tools and hardware simulation techniques.
- Bachelor’s degree in Computer Science, Electronics, or related technical field.
Nice-to-Have Skills
- Hardware interfacing (USB, Ethernet), multimedia interfaces (touch, audio/video).
- Fault-injection and hardware simulation experience.
- Knowledge of peripheral communication protocols (e.g., GMSL, IP).
Job Title: Sr. Automation Engineer
Location: Hillsboro, OR
Duration: Long Term
Job Summary
Panasonic Avionics Corporation is seeking Senior Automation Engineers to lead and enhance advanced automation solutions for embedded and UI-driven systems. The ideal candidates will bring deep expertise in Python-based automation, Robot Framework, and QNX environments, with a strong focus on scalable test architecture, framework migration, and high-volume regression execution. This role requires hands-on technical leadership, cross-layer debugging skills, and collaboration within complex embedded and aviation-grade systems.
Mandatory Technical Skills
(Minimum 5+ years of hands-on experience in each)
- Python automation using Pytest or Robot Framework
- QNX OS (POSIX-compliant systems)
- UX/UI Automation & Testing
Key Responsibilities
- Design, architect, and enhance scalable automation frameworks using Python and Pytest.
- Perform migration of automation assets from Robot Framework to Python/Pytest, ensuring feature parity and long-term maintainability.
- Analyze and interpret large Robot Framework keyword libraries and enable reuse within Python-based executions.
- Optimize hybrid execution models involving both Pytest and Robot Framework assets.
- Develop wrapper layers, fixtures, utilities, and reusable automation components.
- Independently debug complex cross-layer automation issues spanning Python, Robot Framework, QNX OS, and device-level tools.
- Integrate automation frameworks with CI/CD pipelines using tools such as Jenkins, GitLab CI, or Azure DevOps.
- Execute and maintain UI and device automation using Appium, Selenium, or equivalent tools.
- Enforce modular test design principles, including page-object and page-keyword patterns, to ensure long-term automation maintainability.
- Mentor junior engineers and uphold automation design, coding standards, and best practices.
Required Qualifications
- 5+ years of hands-on experience with Python automation and Pytest.
- Strong practical experience with Robot Framework, including keywords, resources, variables, and test structuring.
- Proven experience managing and maintaining large keyword repositories (1000+ keywords).
- Experience working with QNX OS, POSIX systems, Hypervisor-based virtualization, and Cloud environments (AWS).
- Solid understanding of Git version control, branching strategies, and CI/CD workflows.
- Experience with UI and device automation tools such as Appium and Selenium.
- Strong analytical, debugging, and problem-solving skills with the ability to work independently.
- Excellent communication skills and experience working in cross-functional teams.
Preferred Qualifications
- Experience in mobility, embedded systems, aviation, or high-volume regression environments.
- Exposure to automation framework migration, cross-framework interoperability, or keyword reuse models.
- Bachelor’s degree in Computer Science, Electronics, Engineering, or a related field.
Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA
Title: Machine Learning Engineer
Location: San Jose, CA
Responsibilities:
- Productize and optimize models from Research into reliable, performant, and cost-efficient services with clear SLOs (latency, availability, cost).
- Scale training across nodes/GPUs (DDP/FSDP/ZeRO, pipeline/tensor parallelism) and own throughput/time-to-train using profiling and optimization.
- Implement model-efficiency techniques (quantization, distillation, pruning, KV-cache, Flash Attention) for training and inference without materially degrading quality.
- Build and maintain model-serving systems (vLLM/Triton/TGI/ONNX/TensorRT/AITemplate) with batching, streaming, caching, and memory management.
- Integrate with vector/feature stores and data pipelines (FAISS/Milvus/Pinecone/pgvector; Parquet/Delta) as needed for production.
- Define and track performance and cost KPIs; run continuous improvement loops and capacity planning.
- Partner with ML Ops on CI/CD, telemetry/observability, model registries; partner with Scientists on reproducible handoffs and evaluations.
Educational Qualifications:
- Bachelors in computer science, Electrical/Computer Engineering, or a related field required; Master’s preferred (or equivalent industry experience).
- Strong systems/ML engineering with exposure to distributed training and inference optimization.
Industry Experience:
- 3–5 years in ML/AI engineering roles owning training and/or serving in production at scale.
- Demonstrated success delivering high-throughput, low-latency ML services with reliability and cost improvements.
- Experience collaborating across Research, Platform/Infra, Data, and Product functions.
Technical Skills:
- Familiarity with deep learning frameworks: PyTorch (primary), TensorFlow.
- Exposure to large model training techniques (DDP, FSDP, ZeRO, pipeline/tensor parallelism); distributed training experience a plus
- Optimization: experience profiling and optimizing code execution and model inference: (PTQ/QAT/AWQ/GPTQ), pruning, distillation, KV-cache optimization, Flash Attention
- Scalable serving: autoscaling, load balancing, streaming, batching, caching; collaboration with platform engineers.
- Data & storage: SQL/NoSQL, vector stores (FAISS/Milvus/Pinecone/pgvector), Parquet/Delta, object stores.
- Write performant, maintainable code
- Understanding of the full ML lifecycle: data collection, model training, deployment, inference, optimization, and evaluation.
Machine Learning Engineer | Python | Pytorch | Distributed Training | Optimisation | GPU | Hybrid, San Jose, CA
Remote working/work at home options are available for this role.
AI Data & Python Tools Engineer
We're seeking an AI Data and Python Tools Engineer to develop and deploy intelligent tools that leverage big data infrastructure and modern AI architecture. This role combines strong software engineering fundamentals with the ability to build production-ready AI applications at speed, including integration with Model Context Protocol (MCP) systems.
Responsibilities:
- Develop and deploy AI-powered full-stack applications using Python, React, and modern machine learning frameworks
- Design and streamline data pipelines, train and validate ML models, and implement robust evaluation methods
- Collaborate with cross-functional teams to solve complex problems and integrate scalable, cloud-based AI solutions
- Rapidly prototype, test, and iterate on AI tools with a strong focus on performance, flexibility, and scalability
- Maintain clear technical documentation, perform code reviews, and support the full software development lifecycle
Software Engineering & AI/ML Data, Tools Development
- 3+ years of Python Development with a background in back end services and data processing
- Exposure to AI/ML algorithms
- Familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn)
- Understanding of LLMs, vector databases, and retrieval systems
- Experience with Model Context Protocol (MCP) integration and server development
Big Data & Cloud Infrastructure
- Knowledge of building and deploying cloud based applications
- Hands-on experience with cloud data platforms (AWS/GCP/Azure)
- Proficiency with big data technologies (Spark, Kafka, or similar streaming platforms)
- Experience with data warehouses (Snowflake, BigQuery, Redshift) and data lakes
- Knowledge of containerization (Docker/Kubernetes) and infrastructure as code
*Preferred Experience
- Experience building web applications with modern frameworks (React, Vue, or Angular)
- API development and integration experience
- Basic UX/UI design sensibilities for internal tooling
- Experience with real-time data processing and analytics
- Background in building developer tools or internal platforms
- Familiarity with AI/ML operations (MLOps) practices (Experience using airflow)
- Experience building MCP servers and integrating with AI assistants
- Knowledge of structured data exchange protocols and API design for AI systems.
Type: Full Time
Location: Austin, TX or Cupertino, CA (Monday- Friday onsite)
*Relocation assistance can be offered based on individual needs and circumstances*
Qualifications Required A Bachelor's Degree; Graduate Degree preferred At least 3 years of experience with Python Linux / Unix environment experience Experience with PostgreSQL, or other relational databases Able to quickly understand and discuss requirements from Portfolio Managers Preferred Previous experience in low-latency trading environments Familiar with quantitative finance and electronic trading concepts and financial data Equities, futures, FX, or other financial instruments knowledge Experience with containerization and orchestration technologies Experience building and deploying systems that utilize services provided by AWS, GCP or Azure Experience with other programming languages, such as C/C++, Java, Scala, Go, or C# Apache, Confluent Kafka experience Experience automating SDLC pipelines
Title: Full Stack Developer with AI
Duration: 12 Months+
Location: Spring, TX
Type: Onsite
We are seeking a Full Stack Developer who will contribute to building scalable backend services including platform and utility modules application. You will also play an active role in implementing GenAI use cases using modern agentic frameworks.
You will collaborate with product owner, trading fusion developers, data engineers, and other full stack developers across regions.
Responsibilities?:?
- Platform Engineering & Support
- Develop, enhance, and support components of the Global Trading App platform
- Implement monitoring, alerting, and telemetry capabilities using modern observability tools
- Improve platform reliability, scalability, and performance through proactive engineering
- Author infrastructure-as-code using Terraform for cloud resources
Application & Service Development
- Build secure and scalable backend APIs (primarily in Python / FastAPI)
- Create responsive and efficient React-based UI components
- Develop reusable utility modules for fusion teams to accelerate delivery
GenAI & Agentic Solutions
- Implement GenAI-powered features using LLMs, vector databases, and multi-agent frameworks
- Develop “agentic” workflows for automation, troubleshooting, and developer productivity
- Build model integration and evaluation
Collaboration & Standards
- Contribute to engineering best practices and documentation
- Work closely with global trading fusion teams to ensure alignment and technical excellence
Qualifications?:
- Python (advanced): APIs, data processing, async programming
- React: modern component-based UI development
- FastAPI: building high performance backend services
- DBT: data engineering and transformation
- GitHub/CI/CD: strong version control and build pipeline experience
Preferred Skills:
- Terraform, Azure, AWS: infrastructure provisioning and automation
- Databricks, Snowflake
- GenAI / Multi-Agent
- Experience implementing solutions using LLMs, embeddings, prompt engineering
- Familiarity with agentic coding frameworks (e.g., LangChain, AutoGen, OpenAI agents, etc.)
- Understanding of RAG, model orchestration, and AI application patterns
Soft Skills:
- Strong problem-solving skills and ownership mindset
- Ability to work in global, cross-functional teams
- Clear communication and documentation abilities
- Comfort operating in fast-paced, high-availability environments
- Adaptability and willingness to learn new technologies and methodologies
Title: Python with AI(Only w2)
Location: Atlanta GA(Onsite/Only Locals)
Must have mins 10-12 years of overall years of experience
Must haves.
- Strong Python programming (OOP, typing, async programming).
- Experience with API development (FastAPI or Flask).
- PY-test framework knowledge for unit testing.
- Git hub branching familiarity
- Framework development experience with PyTorch, TensorFlow, Hugging Face Transformers, LangChain, OpenAI API
- Basic Cloud knowledge like server less compute, http traffic, CICD concepts
Nice to Have:
- Deep Learning: Neural networks, CNNs, RNNs, transformers, attention mechanisms.
- Azure: resource groups, container apps, vnet, logging, cosmos db.
- SQL (Query writing) experience like SQL server/Azure SQL/Oracle/PostgreSQL
- API security with AuthN/AuthZ understanding of OpenID or oAuth2 flows
If I missed your call ! Please drop me a mail.
Thank you,
Harish
Talent Acquisition
Astir IT Solutions, Inc - An E-Verified Company
Email:
Direct : 7326946000*788
50 Cragwood Rd. Suite # 219, South Plainfield, NJ 07080
Job Title: Embedded Validation Engineer
Location: Charlotte, NC
Job Type: Full-Time
Role Overview
We are seeking a technically strong Embedded Validation Engineer to serve as the Controls and Quality Assurance (QA) point of contact for lab validation and sustaining programs. The role focuses on requirements-based validation, disciplined test execution, defect reporting, and traceability across multiple product programs.
The ideal candidate will work closely with Systems Engineering, Product Development, and QA teams to validate embedded control systems, execute lab testing, and improve test automation and validation processes.
Key Responsibilities
Requirements-Based Validation
- Collaborate with Systems Engineering teams to derive validation strategies and test plans from system requirements.
- Develop and maintain requirement-to-test case traceability.
- Ensure validation activities align with product specifications and engineering requirements.
Lab Test Execution
- Serve as the Controls Validation Point of Contact (POC) for lab validation activities.
- Execute validation tests on prototype hardware and embedded control systems.
- Document test procedures and record pass/fail outcomes with technical accuracy.
Documentation & Traceability
- Maintain organized test documentation including test plans, execution logs, and validation reports.
- Ensure traceability between requirements, test cases, and defect reports.
Defect Reporting & Tracking
- Identify, document, and report defects with clear technical descriptions and reproducible steps.
- Collaborate with development teams to analyze root causes and track defect resolution.
Reporting & Quality Reviews
- Prepare concise 2–3 slide technical summaries of test results and validation findings.
- Present validation updates during PRQRB/SQA or departmental review meetings.
Test Bench & HIL Development
- Design and build test bench setups and Hardware-in-the-Loop (HIL) simulators for validation.
- Support legacy platforms and existing validation environments.
Automation Development
- Contribute to Python-based test automation and validation frameworks.
- Identify opportunities to improve test efficiency through automation.
Product Support & Continuous Improvement
- Support new product development, sustaining engineering, and validation process improvements.
- Drive enhancements in test infrastructure, lab workflows, and validation methodologies.
Required Qualifications
- Bachelor’s degree in Controls Engineering, Software Engineering, Electrical Engineering, or related field.
- 5+ years of experience in embedded systems validation, SQA, or controls testing.
- Strong understanding of Software Quality Assurance (SQA) fundamentals, including test execution and documentation.
- Experience validating embedded control systems and equipment controls.
- Hands-on experience with lab-based validation and prototype testing.
- Knowledge of controls inputs/outputs, sensors, and system interfaces.
- Experience with bench wiring, test setup, and instrumentation.
- Strong analytical skills and familiarity with engineering basics such as heat exchangers and unit conversions.
- Experience with Python scripting and test automation.
Onsite AI Engineer - Construction Industry Focus
New Haven, CT - Onsite 5 days per week
- Initial Assignment: Fully onsite 5 days per week at a construction site in Ft. Myers (FL) or New Haven (CT) for 1 year
- Post-Assignment: Relocation to one of the corporate offices for hybrid employment: Boston, MA (preferred), New York City (NY), New Haven (CT), Herndon (VA), West Palm Beach (FL), or Estero (FL)
Role Summary
As the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.
Responsibilities
- Workflow discovery and redesign: Lead Lean/Six Sigma workshops; map value streams; log high-impact AI agent opportunities that improve field efficiency.
- AI agent development: Build and deploy multiple production-ready AI agents using Copilot Studio, Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks. Integrate agents into Teams/SharePoint on the front end and Databricks Lakehouse or other enterprise data sources on the back end.
- RAG pipelines and LLMOps: Design and operate retrieval-augmented generation (RAG) pipelines with Databricks Delta Tables, Unity Catalog, and Vector Search (or Spark/Hadoop equivalents). Monitor cost, latency, adoption, and model drift.
- Cross-cloud orchestration: Blend OpenAI, Azure OpenAI, and AWS Bedrock services through secure custom connectors to maximize flexibility and adoption.
- Data integration: Partner with Data Engineering to deliver ETL/ELT pipelines, API integrations, and event-driven connectors that feed RAG pipelines and AI agents.
- Change management and adoption: Train field teams, gather feedback, iterate quickly, and embed agents into SOPs. Track usage and ROI with adoption metrics and behavior-change KPIs.
- Stakeholder communication: Translate technical results into business value for leadership and clients. Contribute use cases and playbooks for the “Construction Site of the Future.”
- Compliance and hand-offs: Ensure all AI solutions meet the company’s data governance and security standards. Draft clear user stories and specs for escalation to central AI/Data Engineering teams when necessary.
Qualifications
- 4+ years in AI engineering, data science, or ML-focused software engineering.
- Proven experience building multiple AI agents in production environments.
- 2+ years of hands-on experience with LLMs, RAG pipelines, and LLMOps practices.
- Must have strong traditional software engineering background in Python
Bonus Points
- Experience in construction, manufacturing, or other process-heavy industries.
- Advanced degree in a technical field.
