training engineer

Crescent Steel & Allied Products

<div><div><div><p>Crescent Steel and Allied Products Limited is a multi business organization spread over four campuses with over 500 employees. We are currently inviting applications from dynamic individuals whose values align with ours for the position of Trainee Engineer.
<br>
<br>
This position is responsible for production, production planning, quality management, man management, monitoring and improving manufacturing processes. After successful completion of the training period, the Trainee Engineer will be confirmed as Assistant Engineer. Standard (not exhaustive) requirements of the position are listed below:
</p></div></div><div><div><div><div><div><div><p>Job Title</p>
</div><div><p>Trainee Engineer HSE</p>
</div></div></div><div><div><div><p>Location</p>
</div><div><p>Steel Division, Nooriabad, District Jamshoro</p>
</div></div></div><div><div><div><p>Age</p>
</div><div><p>Maximum 28 Years</p>
</div></div></div><div><div><div><p>Education / Qualification</p>
</div><div><p>BE in Safety/Environment/Mechanical/Industrial/Electrical/Metallurgy; NEBOSH IGC or IOSH preferred</p>
</div></div></div><div><div><div><p>Salary Range (PKR)</p>
</div><div><p>Market Compatible</p>
</div></div></div><div><div><div><p>Experience</p>
</div><div><p>Fresh to 1 Year</p>
</div></div></div><div><div><div><p>Last Date of Application</p>
</div><div><p>June 30, 2026</p>
</div></div></div><div><div><div><p>Job Description</p>
</div><p></p><div><div><ul><li>Acquire sufficient knowledge of the organization&rsquo;s HSE management system through on-the-job training, self learning, and observation of plant activities.</li></ul>
<ul><li>Assist in conducting daily HSE inspections and safety walkthroughs across plant areas.</li></ul>
<ul><li>Support identification and reporting of unsafe acts and conditions.</li></ul>
<ul><li>Assist in Maintaining records of incidents, near misses, risk records, fire equipment inspection record and HSE observations.</li></ul>
<ul><li>Support incident/accident investigations and data collection for root cause analysis.</li></ul>
<ul><li>Assist in implementation and follow-up of corrective and preventive actions (CAPA).</li></ul>
<ul><li>Participate in emergency drills and assist in inspection of firefighting equipment.</li></ul>
<ul><li>Support environmental monitoring and waste management record keeping.</li></ul>
<ul><li>Assist in maintaining HSE documentation in line with ISO 14001, ISO 45001 and applicable legal requirements.</li></ul>
<ul><li>Support HSE training activities, safety talks, and safety awareness initiatives (mock drills, town hall meetings etc.).</li></ul>
<ul><li>Assist in internal and external HSE audits by preparing records and documentation</li></ul>
<ul><li>Coordinate with different departments to follow up on HSE compliance under supervision.</li></ul>
<ul><li>Support monitoring of PPE compliance at site and assist in preparation and maintenance of PPE matrix for different job roles and areas.</li></ul>
<ul><li>Support maintaining HSE KPI dashboards and data analysis for management review.</li></ul>
<ul><li>Help in promoting safety culture through worker engagement and awareness campaigns.</li></ul>
<ul><li>Support HSE team in identifying improvement opportunities and best practices.</li></ul>
<ul><li>Assist in implementation and continual improvement of the integrated QHSE management system (ISO 9001, ISO 14001, ISO 45001, API Q1).</li></ul>
<ul><li>Assist in HSE inventory planning and monitoring of safety equipment and consumables.</li></ul>
<ul><li>Assist in budgeting and cost tracking of HSE function expenditures</li></ul>
<ul><li>Support monitoring of QHSE objectives, targets, and performance indicators.</li></ul>
</div>
<p><b>Terms and Conditions</b></p>
<div>
<ul><li><b>Bond:</b> PKR 300,000 for a period 2 years.</li></ul>
<ul><li><b>Vestment:</b> PKR 6,000/month for a period of 3 years, refundable upon completion.</li></ul>
<ul><li>Relocation to Nooriabad Factory.</li></ul></div><br>
<p></p>
<p>
</p></div></div></div><p></p><div><div><div><p>Skills Required</p>
</div><p></p><div><p><b>Behavioral</b></p>
<ul>
<li>Ethics (Compliance, Fraud, Abuse, Business)</li>
<li>Analytical Thinking</li>
<li>Multi-Tasking</li>
<li>Responsiveness</li>
<li>Enterprising</li>
<li>Problem Solving</li>
<li>Courage and Conviction</li>
<li>Interpersonal Skills</li>
</ul><p></p>
</div><p></p><div><p><b>Technical</b></p>
<ul>
<li>Process Improvement</li>
<li>Quality Assurance and Control</li>
<li>Report Preparations</li>
<li>Development of Procedures/Specifications</li>
<li>Reporting and Analytics</li>
<li>Trouble Shooting</li>
</ul>
<p>IT Skills:</p>
<ul>
<li>MS Office with intermediate level skills across the excel, word and PPT suite</li>
<li>ERP</li>
<li>AutoCAD</li></ul></div></div></div></div></div></div></div><p></p>

Trainee Engineer HSE

Deloitte

<div>
 Three hundred fifty million Americans rely on a healthcare system whose decision-making has become slow, costly, and adversarial - care delayed by prior authorization and paperwork, claims that misfire, clinical decisions made without the right information at the right moment, and patients who struggle to navigate or afford the care they need. Deloitte has a new AI-first effort,, backed by $1B in committed investment, building the reasoning models and agentic systems to rebuild how that system decides - across payers, providers, and life sciences, and for the patients they serve - so that care is faster, fairer, and far less wasteful. This is not AI applied at the margins. It is a ground-up rebuild of the decision-making machinery behind American healthcare, at national scale.
 <br/>
 <br/>
 This is resourced to do real post-training at scale - committed investment in GPU compute and training infrastructure, not toy fine-tunes.
 <br/>
 <br/>
 As a Research Engineer on our post-training team, you will design, train, evaluate, and align the models that reason about healthcare - working across the full post-training lifecycle to shape model behavior for clinical and operational decisioning across the industry. Healthcare decisioning is one of the cleanest verifiable-reward domains outside math and code: the problems are hard. We ground that reward in real signals - clinical policy and criteria, adjudicated outcomes, and clinical-expert judgment - so correctness is checkable rather than asserted.
 <br/>
 <br/>
 You will own the post-training stack for our clinical reasoning models end to end - from data and reward design through trained, evaluated models that ship. This is not a prompt-engineering role. We are looking for people who understand not just how to use LLMs, but how to improve and shape model behavior through advanced post-training.
 <br/>
 <br/>
 You do not need a healthcare background. We pair every engineer with clinical and domain experts and teach you the domain - you bring the modeling depth.
 <br/>
 <br/>
 We hire on demonstrated depth, not years - the level you join at is determined through our interview process, based on the depth and judgment you demonstrate, not your years in a title.
 <br/>
 <br/>
 Work you'll do
 <br/>
 <br/>
 Post-training &amp; alignment
 <br/>
 <br/>
 <ul>
  <li>
   Design and execute post-training pipelines: supervised fine-tuning (SFT), preference optimization, and reinforcement learning / alignment workflows.
  </li>
  <li>
   Build and optimize training using techniques such as SFT, RLHF, PPO, DPO, GRPO, RLAIF, and Constitutional AI, and understand how each affects reasoning quality, safety, latency, cost, and reliability.
  </li>
  <li>
   Train reasoning models for healthcare decisioning using verifiable-reward RL - designing reward signals and verifiers grounded in clinical guidelines, policy and criteria, and adjudicated outcomes.
   <br/>
   <br/>
  </li>
 </ul>
 Reward modeling &amp; data
 <br/>
 <br/>
 <ul>
  <li>
   Develop reward models and preference datasets to improve reasoning quality, factuality, safety, policy adherence, and task performance.
  </li>
  <li>
   Curate, clean, synthesize, and evaluate large-scale instruction, preference, and domain-specific datasets, with rigorous filtering, deduplication, and quality control.
  </li>
  <li>
   Build verification and reward pipelines from our proprietary clinical, claims, and operational data and from clinical-expert labeling - turning guidelines, policy, and adjudicated outcomes into checkable reward signals at scale.
   <br/>
   <br/>
  </li>
 </ul>
 Efficient fine-tuning, training &amp; inference infrastructure
 <br/>
 <br/>
 <ul>
  <li>
   Implement efficient fine-tuning strategies including LoRA, QLoRA, PEFT, and adapter-based approaches; build scalable distributed training using DeepSpeed, FSDP, Megatron-LM, Ray, or equivalent.
  </li>
  <li>
   Optimize inference performance - latency, throughput, quantization, and deployment efficiency - for production, including frameworks such as vLLM, TensorRT-LLM, or TGI.
   <br/>
   <br/>
  </li>
 </ul>
 Small language models &amp; open-weight models
 <br/>
 <br/>
 <ul>
  <li>
   Train and optimize open-weight models such as Llama, Qwen, Mistral, or DeepSeek; build specialized small language models (SLMs) for on-premise and cloud-hybrid deployment with strong performance-per-dollar.
   <br/>
   <br/>
  </li>
 </ul>
 Evaluation, safety &amp; red teaming
 <br/>
 <br/>
 <ul>
  <li>
   Design evaluation frameworks covering reasoning, hallucination detection, factuality, instruction following, structured outputs, and domain-specific metrics.
  </li>
  <li>
   Build healthcare-grade evaluation - held-out clinical benchmarks, deployment regression gates, calibration and uncertainty, factuality against ground truth, and bias/fairness evaluation across patient populations and subgroups - co-designed with clinical experts.
  </li>
  <li>
   Apply PHI/HIPAA-aware data handling and produce model documentation suitable for regulated clinical use.
  </li>
  <li>
   Perform red teaming and adversarial testing to identify alignment failures, unsafe behaviors, jailbreak vulnerabilities, and regression risks; collaborate with agentic and application teams to improve tool use, grounding, and long-horizon reasoning.
   <br/>
   <br/>
  </li>
 </ul>
 The team
 <br/>
 <br/>
 Deloitte brings together AI researchers, modeling and platform engineers, architects, clinical and domain specialists, and product leaders to build, deploy, and operate verticalized AI systems across software, data, models, and cloud infrastructure - engineered for one of the most complex operating environments in the world. The work spans the healthcare industry - payers, providers, and life sciences - and involves genuinely hard reasoning problems, nuanced operational workflows, and a high bar for reliability, with little tolerance for shallow or unreliable outputs. We pair frontier AI research with production-grade engineering, and we ship into real clinical and operational settings rather than leaving models in the lab.
 <br/>
 <br/>
 You can go deep. The team sub-specializes across post-training research, data and reward engineering, and training and inference infrastructure - you won't be expected to own all of it alone.
 <br/>
 <br/>
 <strong>
  Required Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Computational Linguistics, or a related field.
  </li>
  <li>
   Demonstrated depth training and post-training large transformer-based language models in production or research - this is your craft, not coursework or a one-off fine-tune. Genuine depth including SFT and at least one preference-optimization or RL method, evidenced by shipped models, releases, or research.
  </li>
  <li>
   Hands-on experience with reasoning-model training and/or verifiable-reward (RLVR) workflows.
  </li>
  <li>
   Strong understanding of modern post-training techniques: SFT, RLHF, PPO, DPO, GRPO, RLAIF, and preference optimization workflows.
  </li>
  <li>
   Experience with open-weight foundation models such as Llama, Qwen, Mistral, DeepSeek, or equivalent architectures.
  </li>
  <li>
   Strong expertise in PyTorch and modern deep-learning tooling; experience with distributed training frameworks such as DeepSpeed, FSDP, Megatron-LM, or Ray.
  </li>
  <li>
   Experience implementing efficient fine-tuning techniques such as LoRA, QLoRA, PEFT, and quantization-aware workflows.
  </li>
  <li>
   Deep understanding of transformer architectures, tokenization, attention mechanisms, decoding strategies, and model scaling trade-offs.
  </li>
  <li>
   Strong grasp of LLM evaluation methodologies, benchmarking, reward modeling, and alignment trade-offs; experience with large-scale and synthetic datasets, filtering, deduplication, and quality-control pipelines.
  </li>
  <li>
   Strong Python engineering skills and production-grade software practices; ability to work through ambiguous, highly complex technical problems in fast-moving environments.
  </li>
  <li>
   Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.
  </li>
  <li>
   Limited immigration sponsorship may be available.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Preferred Qualifications
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Experience building or optimizing reasoning models, agentic models, or tool-using LLM systems.
  </li>
  <li>
   Familiarity with inference optimization frameworks such as vLLM, TensorRT-LLM, TGI, or Ollama.
  </li>
  <li>
   Experience with multimodal models, speech models, or domain-specific foundation models; experience using large-scale GPU clusters and distributed compute.
  </li>
  <li>
   Contributions to open-source AI projects, research publications, benchmark development, or model releases.
  </li>
  <li>
   Familiarity with safety, governance, and responsible-AI practices; experience in regulated or high-stakes industries such as healthcare, finance, insurance, or public sector.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Compensation
  <br/>
  <br/>
 </strong>
 Base salary is benchmarked to leading technology companies rather than traditional consulting scales, and the role carries a substantial performance-based incentive opportunity designed to grow with the value you help create - startup-style upside, with the backing of a committed, well-capitalized platform. The estimated base salary range is $134,500-$265,100 (not adjusted for geographic differential); actual base pay depends on your skills, experience, and level, and you may also be eligible for a discretionary annual incentive based on individual and organizational performance.
</div>


Research Engineer — Post-Training & Small Language Models (SLMs), Healthcare AI

<div>Three hundred fifty million Americans rely on a healthcare system whose decision-making has become slow, costly, and adversarial - care delayed by prior authorization and paperwork, claims that misfire, clinical decisions made without the right information at the right moment, and patients who struggle to navigate or afford the care they need. Deloitte has a new AI-first effort,, backed by $1B in committed investment, building the reasoning models and agentic systems to rebuild how that system decides - across payers, providers, and life sciences, and for the patients they serve - so that care is faster, fairer, and far less wasteful. This is not AI applied at the margins. It is a ground-up rebuild of the decision-making machinery behind American healthcare, at national scale.<br>
<br>
This is resourced to do real post-training at scale - committed investment in GPU compute and training infrastructure, not toy fine-tunes.<br>
<br>
As a Research Engineer on our post-training team, you will design, train, evaluate, and align the models that reason about healthcare - working across the full post-training lifecycle to shape model behavior for clinical and operational decisioning across the industry. Healthcare decisioning is one of the cleanest verifiable-reward domains outside math and code: the problems are hard. We ground that reward in real signals - clinical policy and criteria, adjudicated outcomes, and clinical-expert judgment - so correctness is checkable rather than asserted.<br>
<br>
You will own the post-training stack for our clinical reasoning models end to end - from data and reward design through trained, evaluated models that ship. This is not a prompt-engineering role. We are looking for people who understand not just how to use LLMs, but how to improve and shape model behavior through advanced post-training.<br>
<br>
You do not need a healthcare background. We pair every engineer with clinical and domain experts and teach you the domain - you bring the modeling depth.<br>
<br>
We hire on demonstrated depth, not years - the level you join at is determined through our interview process, based on the depth and judgment you demonstrate, not your years in a title.<br>
<br>
Work you'll do<br>
<br>
Post-training &amp; alignment<br>
<br>
<ul><li>Design and execute post-training pipelines: supervised fine-tuning (SFT), preference optimization, and reinforcement learning / alignment workflows.</li></ul><br>
<ul><li>Build and optimize training using techniques such as SFT, RLHF, PPO, DPO, GRPO, RLAIF, and Constitutional AI, and understand how each affects reasoning quality, safety, latency, cost, and reliability.</li></ul><br>
<ul><li>Train reasoning models for healthcare decisioning using verifiable-reward RL - designing reward signals and verifiers grounded in clinical guidelines, policy and criteria, and adjudicated outcomes.</li></ul><br>
Reward modeling &amp; data<br>
<br>
<ul><li>Develop reward models and preference datasets to improve reasoning quality, factuality, safety, policy adherence, and task performance.</li></ul><br>
<ul><li>Curate, clean, synthesize, and evaluate large-scale instruction, preference, and domain-specific datasets, with rigorous filtering, deduplication, and quality control.</li></ul><br>
<ul><li>Build verification and reward pipelines from our proprietary clinical, claims, and operational data and from clinical-expert labeling - turning guidelines, policy, and adjudicated outcomes into checkable reward signals at scale.</li></ul><br>
Efficient fine-tuning, training &amp; inference infrastructure<br>
<br>
<ul><li>Implement efficient fine-tuning strategies including LoRA, QLoRA, PEFT, and adapter-based approaches; build scalable distributed training using DeepSpeed, FSDP, Megatron-LM, Ray, or equivalent.</li></ul><br>
<ul><li>Optimize inference performance - latency, throughput, quantization, and deployment efficiency - for production, including frameworks such as vLLM, TensorRT-LLM, or TGI.</li></ul><br>
Small language models &amp; open-weight models<br>
<br>
<ul><li>Train and optimize open-weight models such as Llama, Qwen, Mistral, or DeepSeek; build specialized small language models (SLMs) for on-premise and cloud-hybrid deployment with strong performance-per-dollar.</li></ul><br>
Evaluation, safety &amp; red teaming<br>
<br>
<ul><li>Design evaluation frameworks covering reasoning, hallucination detection, factuality, instruction following, structured outputs, and domain-specific metrics.</li></ul><br>
<ul><li>Build healthcare-grade evaluation - held-out clinical benchmarks, deployment regression gates, calibration and uncertainty, factuality against ground truth, and bias/fairness evaluation across patient populations and subgroups - co-designed with clinical experts.</li></ul><br>
<ul><li>Apply PHI/HIPAA-aware data handling and produce model documentation suitable for regulated clinical use.</li></ul><br>
<ul><li>Perform red teaming and adversarial testing to identify alignment failures, unsafe behaviors, jailbreak vulnerabilities, and regression risks; collaborate with agentic and application teams to improve tool use, grounding, and long-horizon reasoning.</li></ul><br>
The team<br>
<br>
Deloitte brings together AI researchers, modeling and platform engineers, architects, clinical and domain specialists, and product leaders to build, deploy, and operate verticalized AI systems across software, data, models, and cloud infrastructure - engineered for one of the most complex operating environments in the world. The work spans the healthcare industry - payers, providers, and life sciences - and involves genuinely hard reasoning problems, nuanced operational workflows, and a high bar for reliability, with little tolerance for shallow or unreliable outputs. We pair frontier AI research with production-grade engineering, and we ship into real clinical and operational settings rather than leaving models in the lab.<br>
<br>
You can go deep. The team sub-specializes across post-training research, data and reward engineering, and training and inference infrastructure - you won't be expected to own all of it alone.<br>
<br>
Required qualifications<br>
<br>
<ul><li>Bachelor's degree in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Computational Linguistics, or a related field.</li></ul><br>
<ul><li>Demonstrated depth training and post-training large transformer-based language models in production or research - this is your craft, not coursework or a one-off fine-tune. Genuine depth including SFT and at least one preference-optimization or RL method, evidenced by shipped models, releases, or research.</li></ul><br>
<ul><li>Hands-on experience with reasoning-model training and/or verifiable-reward (RLVR) workflows.</li></ul><br>
<ul><li>Strong understanding of modern post-training techniques: SFT, RLHF, PPO, DPO, GRPO, RLAIF, and preference optimization workflows.</li></ul><br>
<ul><li>Experience with open-weight foundation models such as Llama, Qwen, Mistral, DeepSeek, or equivalent architectures.</li></ul><br>
<ul><li>Strong expertise in PyTorch and modern deep-learning tooling; experience with distributed training frameworks such as DeepSpeed, FSDP, Megatron-LM, or Ray.</li></ul><br>
<ul><li>Experience implementing efficient fine-tuning techniques such as LoRA, QLoRA, PEFT, and quantization-aware workflows.</li></ul><br>
<ul><li>Deep understanding of transformer architectures, tokenization, attention mechanisms, decoding strategies, and model scaling trade-offs.</li></ul><br>
<ul><li>Strong grasp of LLM evaluation methodologies, benchmarking, reward modeling, and alignment trade-offs; experience with large-scale and synthetic datasets, filtering, deduplication, and quality-control pipelines.</li></ul><br>
<ul><li>Strong Python engineering skills and production-grade software practices; ability to work through ambiguous, highly complex technical problems in fast-moving environments.</li></ul><br>
<ul><li>Ability to travel 0-50%, on average, based on the work you do and the clients and industries/sectors you serve.</li></ul><br>
<ul><li>Limited immigration sponsorship may be available.</li></ul><br>
Preferred qualifications<br>
<br>
<ul><li>Experience building or optimizing reasoning models, agentic models, or tool-using LLM systems.</li></ul><br>
<ul><li>Familiarity with inference optimization frameworks such as vLLM, TensorRT-LLM, TGI, or Ollama.</li></ul><br>
<ul><li>Experience with multimodal models, speech models, or domain-specific foundation models; experience using large-scale GPU clusters and distributed compute.</li></ul><br>
<ul><li>Contributions to open-source AI projects, research publications, benchmark development, or model releases.</li></ul><br>
<ul><li>Familiarity with safety, governance, and responsible-AI practices; experience in regulated or high-stakes industries such as healthcare, finance, insurance, or public sector.</li></ul><br>
Compensation<br>
<br>
Base salary is benchmarked to leading technology companies rather than traditional consulting scales, and the role carries a substantial performance-based incentive opportunity designed to grow with the value you help create - startup-style upside, with the backing of a committed, well-capitalized platform. The estimated base salary range is $134,500-$265,100 (not adjusted for geographic differential); actual base pay depends on your skills, experience, and level, and you may also be eligible for a discretionary annual incentive based on individual and organizational performance.</div>

QualityKiosk

<p></p><div><div><div><div><div><div><div><ul>MS - Banking &amp; FSSaudi Arabia</ul></div><div><div><div><ul><div><div><div>
Posted On</div><div>
06 Jun 2026</div></div></div><div><div><div>
End Date</div><div>
05 Aug 2026</div></div></div><div><div><div>
Required Experience</div><div>
1 - 1 Years</div></div></div></ul></div></div></div></div></div></div><p></p><div><div><p>Register And </p></div></div></div><p><div><div><div><div><div>Basic Section</div></div></div><div><div><p>
No. Of Openings</p><p>
1</p></div><div><p>
Designation</p><p>
Trainee Test Engineer</p></div><div><p>
Closing Date</p><p>
05 Aug 2026</p></div></div></div><div><div><div><div>
Organisational</div></div></div><div><div><p>
MainBU</p><p>
Quality Engineering</p></div><div><p>
Sub BU</p><p>
MS - Banking &amp; FS</p></div><div><p>
ParentCC</p><p>
COGS</p></div><div><p>
CostCenter</p><p>
COGS</p></div><div><p>
Legal Entity</p><p>
QualityKiosk Technologies Arabia Limited Company</p></div><div><p>
Legal Entity Location</p><p>
Saudi Arabia</p></div><div><p>
Country</p><p>
Saudi Arabia</p></div><div><p>
Region</p><p>
MEA</p></div><div><p>
State</p><p>
Saudi Arabia</p></div><div><p>
City</p><p>
Saudi Arabia</p></div><div><p>
Working Location</p><p>
Saudi Arabia</p></div><div><p>
Client Location</p><p>
NA</p></div></div></div></div></p><div><div><div><div>
Skills</div></div><div><div><p>
Skill</p><div></div><div><div>
 MOB BANKING
</div></div></div><div><p>Highest Education</p><p>
No data available
</p></div><div><p>CERTIFICATION</p><p>
No data available
</p></div><div><p>Working Language</p><p>
No data available
</p></div></div></div></div><div><div><div><div>JOB DESCRIPTION</div></div><p>
&bull; Candidate much have Mobile Banking knowledge. &bull; Assign tasks to the team members &amp; manage workload efficiently &bull; Tracking project milestones and deliverables &bull; Keeping track of new requirements from the project &bull; Coordinate with users for inputs, review and approvals &bull; Responsible for Metrics Measurement and Implementation &bull; Report upon testing activities, including testing results, test case coverage, defects &bull; Ensure adherence to test processes &bull; Daily Defect Discussions &bull; Managing and monitoring work of team</p></div></div></div></div><p></p>

Trainee Test Engineer

SJ Group

<div>
 <strong>
  About SMEC
  <br/>
  <br/>
 </strong>
 <strong>
  Delivering exceptional outcomes starts with having exceptional people.
  <br/>
  <br/>
 </strong>
 SMEC provides unique opportunities to work on iconic industry projects with experienced colleagues and leadership teams. We support and empower employees to drive innovation initiatives within a well-established and growing organization.
 <br/>
 <br/>
 Every employee plays a key role in shaping our business and is driven by teamwork, progressive thinking and creative ideas. We are committed to providing platforms to enable our people to engage in the business, deliver value to clients and develop their careers.
 <br/>
 <br/>
 When you join SMEC, you join a flexible growing organization that has a genuine commitment to CSR, diversity and improving the world we live in.
 <br/>
 <br/>
 <strong>
  The role
  <br/>
  <br/>
 </strong>
 We are looking for a
 <strong>
  Trainee Engineer
 </strong>
 for a Roads and Highways project based in Uthal, Balochistan, Pakistan. The candidate will support the engineering team in day-to-day site and office tasks, assisting in project execution and gaining hands-on experience in civil engineering works.
 <br/>
 <br/>
 <ul>
  <li>
   Assist senior engineers in monitoring and inspecting highway works, including pavements, embankments, and bridges.
  </li>
  <li>
   Support site documentation and preparation of field reports.
  </li>
  <li>
   Coordinate with contractors and sub-contractors for technical clarifications.
  </li>
  <li>
   Assist in material approvals and verification processes.
  </li>
  <li>
   Participate in site meetings and provide updates to senior engineers.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 With a track record of achievement in a related role, you will have gained your experience in a consultancy environment and have a passion for building trusted relationships to drive positive change and win new work.
 <br/>
 <br/>
 <strong>
  Suitable Applicants Will Have/be
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Civil Engineering from a recognized university.
  </li>
  <li>
   Strong willingness to learn and gain practical experience in highway and infrastructure projects.
  </li>
  <li>
   Good organizational and communication skills.
   <br/>
   <br/>
   <br/>
  </li>
 </ul>
 SMEC is an equal opportunity employer. Diversity is a source of strength for our people, our clients, our partners and our communities.
 <br/>
 <br/>
 <strong>
  How To Apply
  <br/>
  <br/>
 </strong>
 All applications must be submitted online and for a confidential discussion regarding this opportunity, please contact
 <strong>
  Taimoor Tariq &ndash;
 </strong>
 Taimoor.tariq@sjgroup.com
 <br/>
 <br/>
 <strong>
  For Further Details About Us, Please Visit Our Website
  <br/>
  <br/>
 </strong>
 https://www.smec.com/
 <br/>
 <br/>
 www.smec.com/careers
 <br/>
 <br/>
 <strong>
  All recruitment activities go through our Recruitment &amp; Talent Team and currently, this role doesn&rsquo;t require agency input. Please do not forward resumes directly to SMEC employees.
  <br/>
  <br/>
 </strong>
 At Surbana Jurong, we put talent, hard work, teamwork and a fun workplace together to approach problems and solve them creatively and collaboratively. Join us in making a positive impact on the world!
</div>


Trainee Engineer

SMEC (an SJ Group company)

<div>
 <strong>
  About SMEC
  <br/>
  <br/>
 </strong>
 <strong>
  Delivering exceptional outcomes starts with having exceptional people.
  <br/>
  <br/>
 </strong>
 SMEC provides unique opportunities to work on iconic industry projects with experienced colleagues and leadership teams. We support and empower employees to drive innovation initiatives within a well-established and growing organization.
 <br/>
 <br/>
 Every employee plays a key role in shaping our business and is driven by teamwork, progressive thinking and creative ideas. We are committed to providing platforms to enable our people to engage in the business, deliver value to clients and develop their careers.
 <br/>
 <br/>
 When you join SMEC, you join a flexible growing organization that has a genuine commitment to CSR, diversity and improving the world we live in.
 <br/>
 <br/>
 <strong>
  The role
  <br/>
  <br/>
 </strong>
 We are looking for a
 <strong>
  Trainee Engineer
 </strong>
 for a Roads and Highways project based in Uthal, Balochistan, Pakistan. The candidate will support the engineering team in day-to-day site and office tasks, assisting in project execution and gaining hands-on experience in civil engineering works.
 <br/>
 <br/>
 <ul>
  <li>
   Assist senior engineers in monitoring and inspecting highway works, including pavements, embankments, and bridges.
  </li>
  <li>
   Support site documentation and preparation of field reports.
  </li>
  <li>
   Coordinate with contractors and sub-contractors for technical clarifications.
  </li>
  <li>
   Assist in material approvals and verification processes.
  </li>
  <li>
   Participate in site meetings and provide updates to senior engineers.
   <br/>
   <br/>
  </li>
 </ul>
 With a track record of achievement in a related role, you will have gained your experience in a consultancy environment and have a passion for building trusted relationships to drive positive change and win new work.
 <br/>
 <br/>
 <strong>
  Suitable Applicants Will Have/be
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor&rsquo;s degree in Civil Engineering from a recognized university.
  </li>
  <li>
   Strong willingness to learn and gain practical experience in highway and infrastructure projects.
  </li>
  <li>
   Good organizational and communication skills.
   <br/>
   <br/>
  </li>
 </ul>
 SMEC is an equal opportunity employer. Diversity is a source of strength for our people, our clients, our partners and our communities.
 <br/>
 <br/>
 <strong>
  How To Apply
  <br/>
  <br/>
 </strong>
 All applications must be submitted online and for a confidential discussion regarding this opportunity, please contact
 <strong>
  Taimoor Tariq &ndash;
 </strong>
 Taimoor.tariq@sjgroup.com
 <br/>
 <br/>
 <strong>
  For Further Details About Us, Please Visit Our Website
  <br/>
  <br/>
 </strong>
 https://www.smec.com/
 <br/>
 <br/>
 www.smec.com/careers
 <br/>
 <br/>
 <strong>
  All recruitment activities go through our Recruitment &amp; Talent Team and currently, this role doesn&rsquo;t require agency input. Please do not forward resumes directly to SMEC employees.
  <br/>
  <br/>
 </strong>
 At Surbana Jurong, we put talent, hard work, teamwork and a fun workplace together to approach problems and solve them creatively and collaboratively. Join us in making a positive impact on the world!
</div>


ROHDE & SCHWARZ GmbH & Co. KG

<div></div><div><div><div><div><div><div><div>Kontakt</div>
<div></div><div><p>Your Rohde &amp; Schwarz recruiting team is looking forward to receiving your application.</p>
</div></div></div></div><div><div><div><div>Info</div>
<div><div><div>Stadt/Region</div>
<div>Maryland (USA)</div>
<div>Einstiegslevel</div>
<div>Berufserfahrene</div>
<div>Besch&auml;ftigungsart</div>
<div>Vollzeit</div>
<div>Ref. Nummer</div>
<div>17061</div></div></div></div></div></div><div></div><div><div><div><br>
<div></div>
</div></div></div></div></div><div></div><div><div><div><div>Join Rohde &amp; Schwarz USA in an impactful technical training role supporting FAA Air Traffic Control communications programs across North America. As a leading supplier of ATC technology in the U.S. and Canada and a trusted partner to air navigation service providers, R&amp;S offers the opportunity to work on complex, mission-critical systems that support safe, reliable operations. Based in Maryland, this role is well suited for a technically credible professional who wants to apply deep technical expertise, influence workforce capability, and help build practical training solutions for a business that is expanding in an important market. This is a hybrid role requiring regular onsite presence in Frederick, MD with occasional travel to Columbia, MD and Coppell, TX to support hands-on training, lab activities, SME collaboration, equipment familiarization, and training delivery.</div>
<h3 class="jobSectionHeader"><b>Your tasks</b></h3>
<ul><li>Serve as a technical training resource for FAA/ATC voice communication systems, helping translate complex technical concepts, system functions, procedures, and field practices into practical learning experiences.</li>
<li>Develop, deliver, and maintain technical training programs for employees/contractors supporting Air Traffic Control (ATC) voice communications, infrastructure, and modernization projects.</li>
<li>Facilitate hands-on learning activities, including lab exercises, equipment walkthroughs, system configuration practice, testing scenarios, troubleshooting exercises, and practical assessments.</li>
<li>Design and update training materials, including lesson plans, presentations, hands-on exercises, job aids, technical manuals, and e-learning content.</li>
<li>Conduct classroom, virtual, and field-based training for engineers, technicians, installers, testers, project managers, and support personnel.</li>
<li>Translate complex technical concepts into clear, practical instruction tailored to diverse audiences and experience levels.</li>
<li>Collaborate with engineering, systems integration, testing, and operations teams to ensure training content reflects current system designs, processes, and best practices.</li>
<li>Develop and administer assessments, practical evaluations, and certification programs to validate employee knowledge and proficiency.</li>
<li>Develop and deliver technical onboarding training for FAA/ATC program personnel.</li>
<li>Facilitate hands-on training involving ATC voice communication systems, network infrastructure, system configuration, testing procedures, and field deployment activities.</li>
<li>Identify training gaps and recommend improvements to enhance workforce capability, technical competency, and operational performance.</li>
<li>Support program readiness activities by ensuring personnel are trained and qualified prior to system deployment and operational turnover.</li>
</ul></div></div></div><div></div><div><div><div><div><h2 class="jobSectionHeader"><b>Exciting insights into Rohde &amp; Schwarz</b></h2>
<div><p>Our colleagues provide insider information about:</p>
<ul><li>Daily adventures and challenges</li>
<li>Our passionate team</li>
<li>The technologies behind the innovative projects and solutions</li>
</ul></div></div></div></div></div><div></div><div><div><div><h3 class="jobSectionHeader"><b>Your qualifications</b></h3>
<ul><li>Bachelor&rsquo;s degree in electrical engineering, Telecommunications, Aviation, or a related field; equivalent technical experience will be considered.</li>
<li>5+ years of experience delivering technical training in a technology, aviation, telecommunications, defense, or related environment.</li>
<li>Experience developing and delivering technical training materials for complex systems and operational environments.</li>
<li>Strong understanding of Air Traffic Control operations, voice communication systems, telecommunications networks, radio systems, or related technologies.</li>
<li>Demonstrated ability to communicate complex technical information clearly and effectively to technical and non-technical audiences.</li>
<li>Experience conducting instructor-led training, virtual training, and hands-on technical workshops.</li>
<li>Strong presentation, facilitation, and public speaking skills.</li>
<li>Experience creating technical documentation, user guides, and training curricula.</li>
<li>Ability to work collaboratively with engineers, technicians, program managers, and product lines.</li>
<li>Understanding of VoIP ED-137 or ATC Tower controller operations preferred.</li>
<li>Willingness and ability to travel up to 20% and work onsite as needed to support technical training, labs, SME collaboration, and program activities. Majority of time will be spent in Frederick, MD with occasional travel to Columbia, MD and Coppell, TX.</li>
<li>In order to be considered, candidates must be a US citizen and able to obtain a US Public Trust Security Clearance.</li>
</ul></div></div></div><div><div><div><h3 class="jobSectionHeader"><b>Interested?</b></h3>
We are looking forward to receiving your application!
<br>
<br>
The total compensation for this position is $76K-$102K. Total compensation includes base salary, variable pay (when applicable) plus benefits. The range is determined by the position, geographic location and level. Individual pay within the range is determined by several factors including location, education or training, relevant work history, sales incentive structure and job-related skills.
<br>
<br>
Rohde &amp; Schwarz is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, disability, protected Veteran status, age or any other characteristic protected by law.
<div>
</div></div></div></div><div><div><div>Rohde &amp; Schwarz is a global technology company with approximately 14,000 employees and three divisions: Test &amp; Measurement, Technology Systems and Networks &amp; Cybersecurity. For 90 years, the company has been developing cutting-edge technology, pushing the boundaries of what is technically possible and enabling customers from various sectors such as business, government and public authorities to maintain their technological sovereignty.</div></div></div></div><div></div>

Technical Trainer - Frederick, MD

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