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Slm Solutions Jobs (NOW HIRING)

TraceLink, Inc

Applied Scientist, GenAI

Wilmington, MA · On-site

You will personally build, iterate, and ship systems focused on LLM/SLM optimization for agentic ... Collaborate with platform and product engineering to ensure solutions are cloud-native, secure ...

Uniphore

Senior Software Engineer - FDE

Palo Alto, CA · On-site

$144K - $190K/yr

Knowledge of SLM Finetuning and Distillation is big advantage. * Experience and knowledge of Agentic development platforms and experience building and delivery enterprise agentic solutions is a huge ...

Generac

Director-Service Technology

Waukesha, WI

For more than 65 years, we've turned big ideas into solutions that help protect homes, strengthen ... Lead functional ownership of SLM, dealer service operations, B2C service applications, technical ...

Mastech Digital

Additive Manufacturing Engineer

Woburn, MA · On-site

$90K - $100K/yr

We are currently seeking an Additive Manufacturing Engineer for our client in the Sealing Solutions ... Responsibilities: - Develop and validate AM processes (DMLS, SLM, EBM). - Optimize designs for ...

Avani Technology Solutions, Inc.

Tech lead

Hartford, CT · On-site

... Drive solution development through requirements gathering, analysis, discovery, business plan ... SLM's policies for throttling - Familiarity in implementing OAuth2.0, SAML, and TLS 1.2 and mutual ...

Avani Technology Solutions, Inc.

Tech Lead

Hartford, CT · On-site

... Drive solution development through requirements gathering, analysis, discovery, business plan ... SLM's policies for throttling - Familiarity in implementing OAuth2.0, SAML, and TLS 1.2 and mutual ...

Noblesoft Technologies

AI Architect

Paramus, NJ · On-site

Lead architecture reviews, technical governance, and design standards. 2. LLM / SLM & Generative AI Solutions * Architect solutions using commercial LLMs such as Gemini, GPT, and Claude. * Design ...

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Slm Solutions information

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How much do slm solutions jobs pay per hour?

As of Jul 16, 2026, the average hourly pay for slm solutions in the United States is $16.13, according to ZipRecruiter salary data. Most workers in this role earn between $14.66 and $15.14 per hour, depending on experience, location, and employer.

What are Slm Solutions?

SLM Solutions is a company specializing in metal additive manufacturing, also known as 3D metal printing. They design and manufacture Selective Laser Melting (SLM) machines, which use laser technology to produce complex metal parts layer by layer from powdered metals. Their equipment is widely used in industries like aerospace, automotive, healthcare, and energy for rapid prototyping and high-performance production. SLM Solutions is known for innovation in the field, offering advanced solutions for efficient and precise metal part fabrication.

What is the difference between Slm Solutions vs 3D Printing Technician?

AspectSlm Solutions3D Printing Technician
CredentialsTypically requires engineering or technical certifications, CAD skillsRequires technical training or certification in 3D printing
Work EnvironmentIndustrial settings, manufacturing facilities, labsManufacturing plants, workshops, labs
Industry UsageUsed in aerospace, automotive, medical device manufacturingUsed across various industries for prototyping and small-batch production

Slm Solutions specializes in industrial metal 3D printing systems, focusing on additive manufacturing technology. 3D Printing Technicians operate and maintain 3D printers, including those from Slm Solutions, and handle the production process. While Slm Solutions is a manufacturer of equipment, 3D Printing Technicians are end-users or operators. Understanding both roles helps clarify the distinction between equipment provider and service provider in the additive manufacturing industry.

What are the key skills and qualifications needed to thrive as an SLM Solutions Engineer, and why are they important?

To thrive as an SLM Solutions Engineer, you need a solid background in mechanical engineering, materials science, or a related technical field, often supported by a relevant degree or experience in additive manufacturing. Familiarity with SLM (Selective Laser Melting) machines, 3D CAD software, and metal powder processing, as well as certifications in additive manufacturing, are highly valuable. Strong problem-solving, project management, and communication skills help you collaborate effectively with clients and cross-functional teams. These competencies are essential to ensure optimal machine performance, high-quality production outcomes, and successful integration of SLM technologies in industrial settings.

What are the typical responsibilities of an engineer working at SLM Solutions, and how do they contribute to additive manufacturing projects?

Engineers at SLM Solutions are typically involved in designing, optimizing, and testing selective laser melting (SLM) systems and metal additive manufacturing processes. Their daily tasks often include collaborating with cross-functional teams such as R&D, production, and quality assurance to develop innovative 3D printing solutions, troubleshoot technical issues, and ensure the reliability of SLM machines. They also work closely with clients to understand application requirements, conduct feasibility studies, and implement custom solutions. This role offers exposure to cutting-edge technology and opportunities for professional growth in the rapidly evolving field of metal additive manufacturing.
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Slm Solutions jobs near you
Infographic showing various Slm Solutions job openings in the United States as of July 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 78% In-person, and 22% Remote job distribution, with an average salary of $33,545 per year, or $16.1 per hour.
Applied Scientist, GenAI

Applied Scientist, GenAI

TraceLink, Inc

Wilmington, MA • On-site

Other

Re-posted 11 days ago

Job description

Staff / Senior Applied Scientist, GenAI & ML Systems

Location: Wilmington, MA (US) - Fulltime Onsite 

About the Role

We are hiring a Staff / Senior Applied Scientist to lead the design and deployment of production-grade GenAI and ML systems with a strong emphasis on being hands-on. You will personally build, iterate, and ship systems focused on LLM/SLM optimization for agentic, multi-agent architectures in cloud environments.

This role is ideal for someone with deep expertise in one or more areas of LLM/SLM optimization for agent-based systems, and hands-on experience in designing, implementing, and operating large-scale multi-agent systems in the cloud.

Key Responsibilities

  • Hands-on ownership of building and shipping multi-agent systems (planner/executor, tool-using agents, supervisor patterns, routing, role-based agents) from prototype to production.

  • Write production-quality code for agent orchestration, tool integration, memory/state design, and context management.

  • Lead context engineering strategies for multi-agent coordination: prompt design, state persistence, agent handoffs, grounding, constraints, and safety controls.

  • Hands-on fine-tune and deploy SLM models for production usage: dataset creation, training workflows, evaluation, and inference serving.

  • Build Advanced RAG pipelines end-to-end, including semantic search, embeddings, hybrid retrieval, and cross-encoder reranking.

  • Implement evaluation frameworks for multi-agent systems covering quality, latency, cost, robustness, and failure mode detection.

  • Collaborate with platform and product engineering to ensure solutions are cloud-native, secure, observable, and scalable (monitoring, logging, CI/CD).

  • Optimize for cost and latency via model routing, caching, compression strategies, and inference efficiency improvements.

  • Mentor peers through code reviews, architecture sessions, and hands-on technical leadership.

Required Knowledge & Experience

  • Context engineering for complex multi-agent systems
    (prompt orchestration, tool calling, memory/state design, routing, constraint handling)

  • Fine-tuning of SLMs and delivering them to production
    (training strategies, validation, deployment, monitoring, rollback readiness)

  • Experience with Advanced RAG, semantic search, embeddings, and cross-encoders
    (retrieval tuning, chunking strategies, query rewriting/planning, reranking)

  • Ability to translate ambiguous requirements into concrete architectures, metrics, and deliverables

  • Hands-on inference optimization experience: quantization, distillation, batching, caching, model routing, speculative decoding

  • Experience building retrieval systems at scale using vector DBs and search stacks

  • Comfort working across the full lifecycle: research prototype A/B test production hardening

Preferred Qualifications

  • Familiarity with enterprise constraints: privacy, security, data governance, permissions, auditability

  • Experience designing and running GenAI observability: traces, prompt/versioning, tool call logging, feedback loops

  • Strong ability to implement production-quality systems in Python (and/or adjacent backend languages)

  • Proven experience deploying GenAI/ML systems in cloud environments (AWS/Azure/GCP)

  • Experience with scalable inference and service operations: containers, APIs, observability, reliability practices

  • MS/PhD in CS/ML/NLP/Stats (or equivalent applied experience building production systems)

Apply