1117 Software Engineer Mobile Developer jobs in Dallas,TX

5+ years of successful business development, sales, or account management experience within the Building Automation Systems (BAS), Controls, HVAC Controls, Energy Services, or Smart Building industry.
Demonstrated success generating new business and closing large commercial projects.
Strong understanding of Building Automation Systems, controls platforms, HVAC systems, energy management, and facility operations.
Proven ability to develop relationships with owners, engineers, consultants, and key stakeholders.
Experience reviewing plans, specifications, and conceptual project requirements.
Strong financial and business acumen with an understanding of project pricing, budgeting, and contract structures.
Excellent presentation, negotiation, and communication skills.
Self-starter with exceptional organizational and time-management abilities.
Ability to manage multiple opportunities simultaneously while maintaining a customer-focused approach.

SmartExplore AI is experimental.

New, Posted 22 hours ago

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Engineer/Sr Engineer, IT Software

American Airlines

Fort Worth, TX 76101

New, Posted just now

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iHire

Machine Learning Engineer

Capital One

Plano, TX 75023

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Principal Engineer - Python API Development

Fidelity Investments

Hurst, TX 76054

~ 31 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

SmartExplore AI is experimental.

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Manufacturing Engineer

Stanley Black & Decker

Farmers Branch, TX 75234

OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelors Degree in Engineering (BSIE / BSME / BSMfgE preferred) or 7+ years equivalent experience (significantly and directly related)
3-5 years of hands-on experience in a manufacturing environment with exposure to CNC turning/milling, Grinding/Polishing and Assembly
Knowledge of Hot or Cold Forging is a plus
Exposure to General Automation, PLC or CNC programming
Experience with process validation, FMEA, and risk assessment
Excellent analytical, structured problem-solving and project management skills
Ability to manage multiple projects simultaneously and work in a team environment
A working knowledge of practical statistics
Proficient with Creo, Catia or AutoCAD and knowledgeable of geometric dimensioning & tolerance
Proficient with MS Word, Power Point and Excel
Excellent written/verbal and presentation skills is a must and communicates effectively with employees at all levels
Earns trust from team members and celebrates successes and is passionate to improve and getting things accomplished
Consistently demonstrates the highest level of personal ethical conduct and leads with integrity and influences through transparency

SmartExplore AI is experimental.