Enigma Jobs in Usa

AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA

Title: AI Research Scientist

Location: San Jose, CA

Responsibilities:

• Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics.
• Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases.
• Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness.
• Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes.
• Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints.
• Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation.
• Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems.
• Contribute to academic publications and represent the company in research communities, as needed.

Educational Qualifications:

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred.
• Candidates with a master’s degree and exceptional research or industry experience will also be considered.

Industry Experience:

• 3–5 years of experience in AI/ML research roles, ideally in applied or product-focused environments.
• Demonstrated success in delivering research-driven solutions that have been deployed in production.
• Experience collaborating in cross-functional teams across research, engineering, and product.
• Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus.

Technical Skills:

• Strong foundational knowledge in machine learning and deep learning algorithms.
• Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO).
• Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases.
• Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations.
• Advanced programming skills in Python (preferred), C++, or Java.
• Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc.
• Strong mathematical foundations in probability, linear algebra, and calculus.
• Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc.
• Ability to translate research insights into roadmaps, technical specifications, and product improvements.

AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA

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

Summary:

Our client is a clinical-stage biotechnology company focused on building the

leading, fully integrated platform for precision genetic medicines. Their approach centers

on developing and refining gene editing and delivery technologies to create effective,

safe treatments. At the core of their work is homology directed repair (HDR), a

proprietary method that allows us to make precise, predictable, and efficient changes to

specific DNA sequences.

By leveraging natural repair processes evolved over time, they maximize safety and

accuracy, enabling a broad range of therapeutic strategies. This foundation supports

their diverse portfolio of HDR-based programs aimed at delivering life-long cures for

serious diseases.

Their first clinical trial, is now approaching Phase II with a novel technology treating

Severe Sickle Cell Disease. Based on Phase 1 data from our first- and best-in-class

true gene correction, they anticipate momentum in the clinical trial with feedback from

FDA on our path towards regulatory approval.

Role:

A high-caliber and detail-oriented Clinical Research Associate (CRA) to

support the execution of the NEW clinical trial, a core clinical program advancing

the company's autologous gene therapy. This is a critical role within our growing

Clinical Operations organization.

As a CRA, you will be responsible for making sure clinical trial sites operate in full

compliance with protocol requirements, regulatory standards, and company's

quality expectations, while maintaining the highest standards of patient safety and data

integrity.

This role is designed for a proactive operator who excels in the operational complexities

associated with advanced therapeutic modalities. The ideal candidate thrives in a fast-

paced startup environment where precision, strong site partnerships, and early

identification of operational risks are essential to successful trial execution.

By overseeing day-to-day site monitoring activities, maintaining inspection-ready

documentation, monitor and verify site compliance with chain-of-identity (COI) and

chain-of-custody (COC) procedures associated with the autologous gene therapy

workflow, and promptly escalate deviations, the CRA plays a vital role in supporting the

successful execution of the NEW study.

Through disciplined site oversight and data quality management, this role enables the

clinical team to generate reliable data and advance company's clinical development

efforts.

Key Responsibilities:

Site Monitoring & Oversight:

o Conduct site qualification, initiation, monitoring (on‐site and remote), and

close‐out visits per the monitoring plan and risk‐based monitoring approach.

o Ensure compliance with protocol, ICH‐GCP, regulatory requirements, and

company SOPs.

o Perform source data review/verification and ensure documentation supports

clinical endpoints.

o Monitor site performance metrics and drive corrective actions with the Clinical

Trial Manager.

Participant Protection & Informed Consent:

o Verify informed consent is properly obtained and documented.

o Ensure ongoing compliance with updated consent forms and protocol

amendments.

o Confirm participant rights, safety, and confidentiality are maintained.

Autologous Gene Therapy Execution (COI/COC):

o Monitor adherence to chain‐of‐identity and chain‐of‐custody processes.

o Oversee compliance with apheresis/cell collection workflows and shipment

procedures.

o Ensure proper handling of temperature‐controlled and cryogenic shipments.

o Coordinate with manufacturing, logistics, and supply chain teams to align

collection and infusion schedules.

Investigational Product ' Materials Accountability:

o Ensure accurate accountability of investigational materials and ancillary

supplies.

o Verify storage conditions, temperature logs, and excursion management.

o Confirm documentation of product receipt, reconciliation, and

return/destruction where applicable.

Data Quality & Systems:

o Review EDC entries for completeness and accuracy.

o Resolve queries with sites and data management.

o Ensure timely and accurate safety reporting including SAEs.

Documentation & Inspection Readiness:

o Ensure investigator site files and trial master file documentation are complete

and inspection ready.

o Maintain accurate monitoring reports and follow‐up documentation.

o Support audit and regulatory inspection readiness activities.

Site Relationship Management & Training:

o Serve as the primary monitoring contact for assigned clinical sites.

o Provide training on protocol procedures, amendments, and operational

workflows.

o Build strong working relationships while maintaining compliance standards.

Qualifications:

Education:

o Bachelor's degree in life sciences, nursing, pharmacy, or related field

required. Advanced degree preferred.

Experience:

o 3+ years of clinical monitoring experience in biotech, pharma, or CRO

environments.

o Experience with cell therapy, gene therapy, oncology, or rare disease trials

preferred.

o Experience coordinating complex clinical logistics or centralized

manufacturing models is a plus.

The right candidate will have:

o Strong understanding of ICH‐GCP and regulatory requirements.

o Experience with EDC, CTMS, and electronic Trial Master File systems.

o Strong organizational skills and attention to detail.

o Ability to collaborate effectively across clinical, regulatory, manufacturing, and

supply chain teams.

Compensation:

The expected base salary range for this position is commensurate with experience and qualifications. Our client offers highly competitive equity participation, a performance-based incentive program, and a comprehensive benefits package designed to support employee well-being and professional growth.

The Quality Assurance team is seeking a Senior Manager, Clinical Quality Assurance to play a key role in connecting clinical development timelines with essential regulatory and CGP requirements.

In this role, Quality is a proactive partner, not just a checkpoint. You will contribute to how clinical studies are designed, executed, and documented by applying your expertise in ICH‑GCP and risk-based, quality-by-design principles. As a core member of cross‑functional teams, including Clinical Sciences, Clinical Operations, and Regulatory Affairs, you will help ensure every study is conducted to the highest global standards.

If you enjoy collaborative problem‑solving, anticipating compliance risks before they surface, and guiding teams through complex international expectations, this role offers the opportunity to make a meaningful impact. You will help strengthen a culture where patient safety, data integrity, and operational excellence guide our decisions.

This position reports to the Associate Director, Quality Assurance – Clinical.

Responsibilities

As the Senior Manager, Clinical Quality Assurance, you will serve as a strategic partner and senior individual contributor responsible for strengthening the integrity of our clinical portfolio. You will drive proactive quality, risk-based oversight, and regulatory readiness across global studies through the following areas:

Strategic Study Leadership (Daily / Ongoing)

• Serve as the CQA representative on Study Execution Teams.
• Identify quality and compliance risks during protocol and study planning.
• Lead or support RCA discussions and recommend effective CAPAs.

Risk Based Audits & Vendor Oversight (Monthly / Quarterly)

• Plan and conduct investigator site, CRO, and internal process audits.
• Prepare clear audit reports that inform study and vendor decisions.
• Act as the quality point of contact for CRO partners and support ongoing governance.

Inspection Readiness & Regulatory Alignment (Project Based)

• Support mock inspections and global health authority readiness activities.
• Prepare SMEs for FDA, EMA, and other inspections.
• Monitor evolving ICH E6(R3)/GCP guidance and update procedures accordingly.

Mentorship & Quality Systems (Continuous)

• Provide technical guidance to junior team members, contractors, and third party auditors.
• Contribute to the development and optimization of Clinical and Quality SOPs and quality metrics.

Budget & Resource Planning

• Support QA leadership in planning audit resources based on study risk and geographic needs.

What We’re Looking For

• Bachelor’s degree in life sciences or related field with 10+ years of industry experience, or an advanced degree with 7+ years of relevant experience
• 5+ years of direct experience in Clinical Quality Assurance or Clinical Compliance
• Proven experience leading Phase 1-III GCP audits and executing risk‑based audit plans
• Hands-on experience with QMS and eTMF systems (e.g., Veeva Vault)
• Strong ability to interpret ICH E6(R3) and 21 CFR Part 11 and translate them into practical quality strategies
• Demonstrated expertise in Root Cause Analysis (RCA) to development of sustainable CAPAs
• Comprehensive knowledge of global GCP regulations; recognized as subject matter resource for cross-functional teams
• Strong collaboration and communication skills; able to influence partners while upholding quality expectations
• Comfortable navigating ambiguity and applying sound judgment in complex clinical situations

Additional Valued Skills and Experiences:

While the following are desired, they are not required. We encourage you to apply even if you do not meet every qualification listed.

• Professional certifications such as RQAP‑GCP, ASQ‑CQA, Six Sigma.
• Experience supporting Nephrology or Small Molecule clinical programs.
• Prior experience in Clinical Operations